The HEB Data Scientist interview guide, interview questions, salary data, and interview experiences.

HEB Data Scientist Interview Guide

Getting ready for an Data Scientist interview at HEB? The HEB Data Scientist interview span across 10 to 12 different question topics. In preparing for the interview:
<ul>
<li>Know what skills are necessary for HEB Data Scientist roles.</li>
<li>Gain insights into the Data Scientist interview process at HEB.</li>
<li>Practice real HEB Data Scientist interview questions.</li>
</ul>
Interview Query regularly analyzes interview experience data, and we've used that data to produce this guide, with sample interview questions and an overview of the HEB Data Scientist interview.


Getting ready for an Data Scientist interview at HEB? The HEB Data Scientist interview span across 10 to 12 different question topics. In preparing for the interview:

- Know what skills are necessary for HEB Data Scientist roles.
- Gain insights into the Data Scientist interview process at HEB.
- Practice real HEB Data Scientist interview questions.

Interview Query regularly analyzes interview experience data, and we've used that data to produce this guide, with sample interview questions and an overview of the HEB Data Scientist interview.
        

Overview

Challenge

We've gathered this data from parsing thousands of interview experiences sourced from members.

We've gathered this data from parsing thousands of interview experiences sourced from members.

HEB Data Scientist Interview Process

Machine Learning

Bagging vs Boosting

Regularization and Validation

Replaced by QUESTION 791 - Should be deleted

Bias Variance Tradeoff

Youtube Recommendations

Xgboost vs Random Forest

Forecasting & Time Series

Significance Time Series

Why Do We Need Time Series Models?

Time Series Discrepancies

Brainteasers

How would you answer when an Interviewer asks why you applied to their company?

Why Do You Want to Work With Us

What do you tell an interviewer when they ask you what your strengths and weaknesses are?

Your Strengths and Weaknesses

Data Structures & Algorithms

Write a function to find the best days to buy and sell a stock and the profit you generate from the sale.

Buy or Sell

Given a string, write a function to find its first recurring character.

Recurring Character

Statistics

What are the assumptions of linear regression?

Assumptions of Linear Regression

When an interviewer asks you a question along the lines of:

<ul>
<li>Why did you apply to our company?</li>
<li>What are you looking for in your next job?</li>
<li>What makes you a good fit for our company?</li>
</ul>

How should you respond?

When asked 'What are you looking for in your next job?' in an interview, how can you tie the company's employee benefits into your response?

When asked 'What are you looking for in your next job?' in an interview, how can you tie the company's employee benefits into your response?

Why Do You Want to Work With Us I

How can company values be used effectively in an interview when asked 'What makes you a good fit for our company?'

How can company values be used effectively in an interview when asked 'What makes you a good fit for our company?'

Why Do You Want to Work With Us II

When responding to the question 'Why did you apply to our company?' during an interview, what aspect should you highlight?

When responding to the question 'Why did you apply to our company?' during an interview, what aspect should you highlight?

Why Do You Want to Work With Us III

When an interviewer asks a question along the lines of:

<ul>
<li>What would your current manager say about you? What constructive criticisms might he give?</li>
<li>What are your three biggest strengths and weaknesses you have identified in yourself?</li>
</ul>

How would you respond?

When asked about your strengths in an interview, what is an effective way to respond?

When asked about your strengths in an interview, what is an effective way to respond?

Your Strengths and Weaknesses I

Which of the following is an acceptable strategy when discussing weaknesses in an interview?

Which of the following is an acceptable strategy when discussing weaknesses in an interview?

Your Strengths and Weaknesses II

What are the assumptions of linear regression?

Which assumption of the residuals of the standard linear regression model can not be overcome by increasing the sample size?

Regression assumptions

Let’s say that you’re training a classification model.

How would you combat overfitting when building tree-based models?

Let's say that you're training a classification model.   How would you combat overfitting when building tree-based models?

Overfit Avoidance

Let’s say we’re comparing two machine learning algorithms. In which case would you use a bagging algorithm versus a boosting algorithm? 

Give an example of the tradeoffs between the two.

In machine learning, when would you use a bagging algorithm over a boosting algorithm?

In machine learning, when would you use a bagging algorithm over a boosting algorithm?

Bagging vs. Boosting

Imagine you are asked to build a machine learning model to decide new loan approvals for a
financial firm. You ask the data department in the company for a subset of data to get started
working on the problem. The data includes different features about applicants such as age,
occupation, zip code, height, number of children, favorite color, etc. You decide to build
multiple machine learning models to test out different ideas before settling on the best one.

How would you explain the bias-variance tradeoff with regards to
building and choosing a model to use?

Bias vs. Variance Tradeoff

Explain the difference between the XGBoost and random forest algorithms and give an example where you would use one over the other.

Why might a data scientist choose to use XGBoost instead of Random Forest for a particular machine learning task?

Why might a data scientist choose to use XGBoost instead of Random Forest for a particular machine learning task?

XGBoost vs Random Forest: Choice

Regularization and cross-validation are two common techniques used to improve the performance of machine learning algorithms.

When should you use one versus the other?

Given the choices below, which one is an example of a scenario where we should be using regularization?

Given the choices below, which one is an example of a scenario where we should be using regularization?

Regularization Example

What’s the relationship between PCA and K-means clustering?

What does the variable “k” in k-means clustering refer to?

What does the variable "k" in k-means clustering refer to?

Input of K-means

PCA and K-Means

How would you explain the bias variance tradeoff in machine learning to a high school student?

What are time series models? Why do we need them when we have less complicated regression models?

What can happen if a traditional regression model is used on data that has autocorrelation?

What can happen if a traditional regression model is used on data that has autocorrelation?

Why Do We Need Time Series Models? I

Why can't standard regression models be used effectively for data points where current values are influenced by past values?

Why can't standard regression models be used effectively for data points where current values are influenced by past values?

Why Do We Need Time Series Models? II

Let’s say that you’re working at a global trading company and you’re analyzing the price of a particular asset over time. This dataset is super noisy, volatile, and you’re not guaranteed completely accurate data.

How would you analyze this data to ensure there aren’t any discrepancies?

Let’s say you have a time series dataset grouped monthly for the past five years.

How would you find out if the difference between this month and the previous month was significant or not?

Given a string, write a function <code>recurring_char</code> to find its first recurring character. Return <code>None</code> if there is no recurring character.

Treat upper and lower case letters as distinct characters.

You may assume the input string includes no spaces.

Example 1:

Input:

<pre tabindex="0" class="chroma"><code>input = &#34;interviewquery&#34;
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>output = &#34;i&#34;
</code></pre>

Example 2:

Input:

<pre tabindex="0" class="chroma"><code>input = &#34;interv&#34;
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>output = None
</code></pre>

Let’s say you’re tasked with building the YouTube video recommendation algorithm.

How would you design the recommendation system?

What are important factors to keep in mind when building the recommendation algorithm?

You work as a data scientist for a grocery store chain that has a mobile app. At the end of the checkout process on the app, users are presented with an up-sell carousel, a sliding display of items that users can scroll/swipe to view and add to their cart. Currently, the carousel only presents items from the store’s personal brand.

How would you determine whether the carousel should replace store-brand items with national-brand products of the same type?

How would you determine whether the carousel should replace store-brand items with national-brand products of the same type?

Upsell Carousel

A/B Testing

Given a list of <code>stock_prices</code> in ascending order by <code>datetime</code>, and their respective dates in list <code>dts</code>, write a function <code>max_profit</code> that outputs the max profit by buying and selling at a specific interval and start and end dates to buy and sell for max profit.

Example:

Input:

<pre tabindex="0" class="chroma"><code>stock_prices = [10,5,20,32,25,12]
dts = [
 &#39;2019-01-01&#39;, 
 &#39;2019-01-02&#39;,
 &#39;2019-01-03&#39;,
 &#39;2019-01-04&#39;,
 &#39;2019-01-05&#39;,
 &#39;2019-01-06&#39;,
]

def max_profit(stock_prices,dts) -&gt; 27
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def max_profit(stock_prices, dts) -&gt; 
(27, &#39;2019-01-02&#39;, &#39;2019-01-04&#39;)
</code></pre>

You are a chef preparing for an important event. You downloaded three recipes to make and imported each as a separate table: <code>recipe1</code>, <code>recipe2</code>, <code>recipe3</code> into your database. Each recipe requires some grocery items in various quantities.

Write a query that sums up the total mass of each grocery item required across all recipes.

Input:

<code>recipe1</code> table:

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>grocery</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>mass</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
<code>recipe2</code> table:

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>grocery</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>mass</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
<code>recipe3</code> table:

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>grocery</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>mass</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
Output:

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>grocery</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>total_mass</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>

Write a query to generate a shopping list that sums up the total mass of each grocery item required across three recipes.

Generate Shopping List from Recipes

A manager in a packet filling line is complaining that their machine is not functioning correctly. The machine weighs a group of packets at once and attempts to get 25 packets into a box.

He has been getting complaints from customers that the boxes contain amounts other than 25. How would you help out?

Incorrect Packets

Business Case

HEB Data Scientist Interview Questions

<div><h2>Corporate Planning & Analysis</h2>Responsibilities: Corporate Planning & Analysis develops/maintains budgets and financial systems while providing current, reliable financial data, analysis, and technical info. As a Business Analyst I, you'll perform research work and prepare financial analysis to make essential corporate planning decisions. Once you're eligible, you'll become an owner in the company, so we're looking for commitment, hard work, and focus on quality and customer service. 'Partner-owned' means our most important resources--people--drive the innovation, growth, and success that makes H-E-B The Greatest Retailing Company. Do you have a: HEART FOR PEOPLE... interpersonal and influencing skills? HEAD FOR BUSINESS... analytical mindset and the ability to communicate findings? PASSION FOR RESULTS... drive to produce work that impacts decisions and results?We are looking for:<ul><li>a related degree or comparable formal training, certification, or work experience</li><li>experience in retail or business analysis</li></ul>What is the work?<ul><li>Analytics: Applies knowledge gained from experience to provide credible, action-oriented analyses and recommendations to management</li><li>Provides business unit-focused reporting that includes data related to sales, cogs, ad-loss, clearance and markdowns, shrink and procurement revenue involving trend analysis, macro/micro economic research, and comparable analysis, etc.</li><li>Works on strategic ad hoc projects, to assist BUDs and BDMs in business decision-making</li><li>Supports BUDs and BDMs in improving their businesses through enhanced processes and detailed financial analysis and interpretation</li></ul>What is your background?<ul><li>A related degree or comparable formal training, certification, or work experience</li><li>1+ years of experience in retail or business analysis</li><li>Experience applying retail accounting and finance principles to development of costing/forecasting models</li></ul>Do you have what it takes to be a fit as an H-E-B Business Analyst I?<ul><li>Working knowledge of business and retail accounting and finance principles</li><li>Strong analytical skills</li><li>Strong interpersonal skills</li><li>Strong verbal/written communication and presentation skills</li><li>Intermediate PC skills</li><li>Ability to effectively work at all levels of the organization</li><li>Ability to successfully communicate with and influence upper-level management</li><li>Ability to produce work products that make an impact on management decisions and business results</li><li>Ability to manage large-scale projects from conception to implementation</li><li>Ability to work effectively and efficiently with little supervision</li><li>Self-directed and motivated to independently accomplish results</li></ul>Can you...<ul><li>Function in a fast-paced, retail, office environment</li><li>Travel by car or plane with overnight stays</li><li>Sit for extended periods</li><li>Work extended hours</li></ul>11-2017 PROC3232</div>

<div><h2>Senior Product Manager, Data Platform</h2>Responsibilities Since H-E-B Digital Technology's inception, we've been investing heavily in our customers' digital experience, reinventing how they find inspiration from food, make food decisions, and ultimately get food into their homes. This is an exciting time to join H?E?B Digitalwe're using the best available technologies to deliver modern, engaging, reliable, and scalable experiences to meet the needs of our growing audience. As a Senior Product Manager, Data Platform you'll deliver platforms and products that ensure a compelling digital experience for our retail Customers or help arm H?E?B Partners company-wide with world-class business applications to thrive in their jobs. You'll collaborate with business stakeholders to cultivate an intimate understanding of their needs and technology and drive the entire technology project lifecycle to make our digital tools work. This role requires strong subject-matter expertise in modern data platforms, including how data is ingested, processed, governed, secured, and delivered across complex enterprise ecosystems. Once you're eligible, you'll become an Owner in the company "Partner-owned" means our most important resourcesPeopledrive the innovation, growth, and success that make H?E?B The Greatest Omnichannel Retailing Company. Do you have a: HEART FOR PEOPLE skills to cultivate an intimate understanding of customer needs? HEAD FOR BUSINESS ability to apply rigorous logic / methods to solve difficult problems? PASSION FOR RESULTS drive to negotiate solutions without damaging relationships? We are looking for: Experienced product manager who is curious, empathetic, and data-driven, with strong business acumen related to enterprise organizations, and can apply those skills to the delivery of technology solutions for Partners, Suppliers and Customers. What is the work? Digital Product Management: Apply deep knowledge of data platform capabilitiesincluding data ingestion, storage layers (raw/silver/gold), orchestration, and consumption patternsto define and deliver scalable platform experiences. Partner closely with data engineering, platform engineering, governance, and analytics teams to shape a cohesive platform strategy. Ensure platform capabilities align with enterprise data governance standards, including data quality, metadata management, and secure access practices. Advocate for frictionless developer and analyst experiences by understanding how platform components interact end-to-end. Manages activities that drive product development and delivery at the team / department level; serves as dedicated owner of a set of related products. Serves as subject matter expert on owned product areas. Guides project vision; coordinates cross-functional teams of Partners / suppliers. Explores / validates and executes with little pre-defined solutions; makes independent decisions based on analysis, experience, judgment. May mentor product managers or business analysts. Collaborates with stakeholders company-wide to understand / document end-to-end business needs. Builds and owns product roadmaps. Accesses / organizes data; builds analyses to understand financial impact of business opportunities. Works closely with business customers, Product Managers, Design, and Engineering Partners to drive the entire product lifecycle. Manages relationships with key stakeholders to drive and enhance product vision and strategy. Drives teams to demonstrate high velocity, efficiency, and morale; ensures commitments are met. Identifies critical risks and dependencies; anticipates / resolves issues with little escalation. Creates quantitative data analysis and modeling to inform outcomes; defines methods / metrics for success. May manage / supervise Product Managers. What is your background? A related degree or comparable formal training, certification, or work experience 5+ years of experience in product management / development supporting data platforms Hands-on knowledge of enterprise data platforms or cloud-based data ecosystems (e.g., ingestion frameworks, lake/lakehouse, streaming, orchestration, observability) Experience enabling data engineers, data scientists, and analysts through platform capabilities Familiarity with data governance, including data quality, metadata, access controls Comprehensive knowledge of voice of the customer and product management tools (JIRA, Confluence) Advanced analytical, communication, and presentation skills Strong Agile / Scrum skills Strong negotiating, interpersonal, influencing, and collaboration skills Strong decision-making skills Ability to leverage data to tell a meaningful story Ability to break down complex problems and improve efficiency Ability to translate technical concepts for business audiences Adaptability and ability to affect change Motivated to independently achieve results Can you Work collaboratively across a complex enterprise and evolving business Occasionally work extended hours</div>

Company Name : Willware TechnologiesExperience : 10+ Years Location : Bangalore Work Mode : Onsite Role : Senior Data Scientist Roles and Responsibilities Important Key words:-<ul><li>Large Language Models (LLMs)</li><li>Classical Machine Learning (Supervised & Unsupervised Learning)</li><li>Generative AI</li><li>Python</li><li>Microsoft Azure</li><li>Azure Data Factory & Azure Data Foundry</li></ul> Your main responsibilities will include<ul><li>Design, develop, and deploy predictive models including forecasting, classification, regression, and segmentation</li><li>Build and customize deep learning NLP models, multimodal models (text + vision), and context‑aware AI solutions.</li><li>Implement and tune custom loss functions, advanced quantitative methods, and high‑impact ML algorithms.</li><li>Deep knowledge of statistical modeling, experimentation, and advance data analysis.</li><li>Conduct rigorous model validation, diagnostics, and performance monitoring.</li><li>Perform complex statistical analyses and generate meaningful insights that influence business strategy.</li><li>Work closely with product managers, engineering teams, and business leaders to define analytical requirements.</li><li>Conduct A/B testing, causal inference, and optimization modeling (linear, mixed‑integer, multi‑objective).</li><li>Translate ambiguous business needs into clear analytical frameworks and modeling approaches.</li><li>Define and track KPIs and product metrics, supporting data driven prioritization and roadmaps.</li><li>Exposure to agentic AI workflows leveraging LLMs, retrieval, tool use, and reasoning systems. </li></ul> You have the needed skills and qualities to work in analytics, including:<ul><li>Strong proficiency in Python (Pandas, NumPy, Scikit‑learn; TensorFlow/PyTorch preferred).</li><li>Expertise in SQL, relational databases, data warehouses.</li><li>Hands‑on experience with Databricks, large‑scale analytics, and ML workflows.</li><li>Deep knowledge of statistical modeling, experimentation, and causal analysis.</li><li>Experience working with Azure cloud services.</li></ul> The following skills are considered distinct advantages: <ul><li>Work with large‑scale datasets including 1 TB+ data processing for analytics and modeling tasks.</li><li>Build, optimize, and maintain data pipelines using Databricks, MLflow, and cloud‑native tooling.</li><li>Develop data engineering scripts (e.g., parsers, transformers) required for ML dataset preparation.</li><li>Integrate, clean, preprocess, and validate data from multiple sources ensuring governance, accuracy, and compliance</li></ul>

afarax is looking for a freelance Data Scientist. We need you! The project:Our client in the banking sector, is seeking an experienced Data Scientist to strengthen their team. Function description:<ul><li>Tackle various business challenges by creating responsible AI models to answer the needs of the Marketing and Communication to make campaigns more relevant and impactful.</li><li>Capture the business needs, determine the feasibility, build the models and analyses to identify the most relevant target groups and set up tests to measure the impact of the models</li><li>Build models to support customer journey driven marketing campaigns</li><li>Build pipelines that clean and structure web analytics data and use LLMs to detect customer intent</li><li>Apply the guidelines and best practices (e.g. explainability) for building the responsible AI models. Monitor and deploy AI models in production using a comprehensive stack of tools.</li><li>Present technical concepts into clear, actionable insights to business owners and advise about the usage of the models in the campaigns.</li></ul> Is this you?Language requirements: <ul><li>English: Fluent spoken and written</li><li>Dutch: Fluent spoken and written</li></ul>OR<ul><li>French: Fluent spoken and written</li></ul> You have at least 5 years of relevant experience Technical experience : Mandatory<ul><li>Expert in Python programming and Python data science environment (scikit learn, PyTorch, TensorFlow)</li><li>Expertise in customer journey modeling (e.g. next best action)</li><li>Solid understanding of statistical methods, experiment design and machine learning algorithms (traditional and deep learning)</li><li>Expertise in usage of LLMs for text classification, interpretability, guardrails and validation of LLM driven predictions</li><li>git, bash</li><li>SQL</li></ul> Technical experience : Preferable<ul><li>Experience with incremental learning</li><li>Experience with uplift modeling</li><li>Experience with Marketing Mix Modeling, optimization under constraints</li><li>SAS</li><li>Streamlit</li></ul> Soft skills:<ul><li>Taking ownership and ability to drive projects end-to-end with minimal guidance</li><li>Ability to translate data insights into actionable business recommendations</li><li>Quick learner and autonomous</li><li>Clear and concise communication</li><li>Team player</li><li>Pro-active attitude and result driven</li><li>Analytical and problem-solving mindset</li></ul> How afarax supports you?<ul><li>You benefit from our extensive network</li><li>You will have access to projects that fit your expertise</li><li>We help and support you throughout your project</li><li>We offer the possibility to build a valuable and lasting partnership</li></ul>Check out more projects on: <a>https://afarax.be/jobs/type/freelance/</a>

afarax is looking for a freelance Data Scientist – Machine Learning. We need you! The project:Our client in the banking sector, is seeking an experienced Data Scientist – Machine Learning to strengthen their team. The data scientist will be responsible for:<ul><li>Designing, developing and deploying machine learning models for predictive analytics and data-driven use cases</li><li>Working with large datasets to extract insights and support business decision-making</li><li>Building and optimizing data pipelines and ML workflows in collaboration with data engineering teams</li><li>Developing solutions using Python-based ML frameworks</li><li>Working with cloud-based data platforms, particularly within Azure environments</li><li>Leveraging PySpark for large-scale data processing and distributed computing</li><li>Contributing to data exploration, feature engineering and model evaluation</li><li>Supporting the industrialization and deployment of models into production environments</li><li>Collaborating with business stakeholders to translate business needs into data science solutions</li><li>Participating in the continuous improvement of data science methodologies and best practices</li></ul> Is this you?Technical SkillsRequired:<ul><li>Python</li><li>Machine Learning (supervised / unsupervised learning)</li><li>Data analysis and statistical modelling</li><li>Azure data ecosystem</li><li>PySpark / distributed data processing</li><li>Experience working with large datasets and data pipelines</li></ul>Nice to have:<ul><li>Generative AI (LLMs, NLP, GenAI frameworks)</li><li>Experience with ML model deployment and MLOps practices</li><li>Experience with modern data platforms (Databricks, Spark environments)</li></ul> Business KnowledgeExperience in the financial sector is considered a strong asset, particularly in domains such as:<ul><li>Banking</li><li>Finance</li><li>Risk</li><li>Compliance</li></ul>Understanding regulated environments and financial data use cases is beneficial. Profile<ul><li>2 to 7 years of experience as a Data Scientist or in a similar role</li><li>Strong analytical mindset and problem-solving skills</li><li>Ability to work with complex datasets and translate insights into business value</li><li>Comfortable working in cross-functional teams with data engineers, analysts and business stakeholders</li><li>Curious, proactive and eager to explore new technologies in the AI and data domain</li></ul> How afarax supports you?<ul><li>You benefit from our extensive network</li><li>You will have access to projects that fit your expertise</li><li>We help and support you throughout your project</li><li>We offer the possibility to build a valuable and lasting partnership</li></ul>Check out more projects on: <a>https://afarax.be/jobs/type/freelance/</a>

Fiddlehead Technology is a Canadian leader in advanced analytics and AI-driven solutions, helping global companies unlock value from their data. We specialize in applying machine learning, predictive forecasting, and Generative AI to solve complex business problems and empower smarter decision-making. Our culture thrives on innovation, collaboration, and continuous learning. We invest in our people by offering structured opportunities for professional development, a healthy work-life balance, and exposure to cutting-edge AI/ML projects across industries. At Fiddlehead, employees are encouraged to explore, create, and grow while contributing to high-impact solutions. The Role This high-impact leadership position in Gurugram guides our Indian Data Scientists and ML Engineers while collaborating with Canadian HQ and global teams. Reporting to Chief Data Scientist (in Canada), you'll own end-to-end delivery of ML/GenAI solutions for CPG manufacturing, supply chain, and marketing, driving business impact while building Fiddlehead's India practice from the ground up. Key Responsibilities Delivering Business Value <ul><li>Own end-to-end delivery of high-quality machine learning, GenAI, and analytics solutions aligned with business and strategic objectives </li><li>Lead advanced analytics projects uncovering insights for demand forecasting, production optimization, competitor analysis </li><li>Communicate data stories effectively from developers to C-suite stakeholders </li><li>Develop scalable solutions for commercial, manufacturing and supply chain functions </li><li>Coach and mentor team members, on best practices both technically and business oriented, aligned to Fiddlehead’s core values (Diversity, Accountability, Transparency, Accuracy) </li><li>Operational and people management responsibilities as needed </li></ul>Building Data-Driven Culture <ul><li>Lead user groups, adoption initiatives, knowledge sharing </li><li>Establish and scale Fiddlehead India's Data Science & AI practice (hiring, methodology, knowledge transfer from Canada, etc.) </li></ul>Talent Development <ul><li>Mentor/coach team in India towards success and growth (Foster continuous improvement, share best practices </li><li>Design onboarding/upskilling programs accelerating India team self-sufficiency </li><li>Align capabilities with strategic goals + individual growth paths </li></ul>Operational Excellence <ul><li>Manage resources/project prioritization aligned with company strategy </li><li>Oversee MLOps, model deployment, monitoring (data drift, concept drift, performance) </li><li> Ensure governance, standards, best practices for India </li><li>Track KPIs measuring practice maturity and business impact </li></ul> Required Qualifications <ul><li>10+ years Data Science, data engineering, or applied analytics experience </li><li>Bachelor's degree in quantitative field (Statistics, CS, Engineering, Math); Master's/PhD preferred </li><li>5+ years managing people/projects </li><li>7+ years Python + software development best practices </li><li>Experience with cloud ML platforms such as Azure & Databricks) </li><li>Strong communication + passion for data-driven problem solving </li></ul>Preferred Qualifications <ul><li>CPG experience (sales, marketing, supply chain, manufacturing) </li><li>Proven ability thriving in ambiguity, managing competing priorities (Agile/Waterfall) </li><li>Experience scaling DS/AI practices in India/international teams </li></ul> We carefully review every application and are committed to providing a response. All hiring decisions are made by people. We may use AI-based tools to assist with the initial review of applications by ranking candidates based on job-relevant criteria. These tools support but do not replace human judgment. Candidates selected will be invited to an in-person or virtual interview. To ensure equal access, we provide accommodations during the recruitment process for applicants with disabilities. If you require accommodations, please reach out to our team through the contact page on our website. At Fiddlehead, we are dedicated to fostering an inclusive and accessible environment where every employee and customer is respected, valued, and supported. We welcome applications from women, Indigenous peoples, persons with disabilities, ethnic and visible minorities, members of the LGBT+ community, and others who can help enrich the diversity of our workforce. We offer a competitive compensation package, flexible hybrid work arrangements, and opportunities to contribute to impactful projects. Employees benefit from mentorship, training, and active participation in AI communities, all within a collaborative culture that values innovation, creativity, and professional growth.

<h3>Job Description</h3><div>Job Description<div>What Impact You'll HaveOur team is charged with taking commercial and academic innovation high-side, in domains of Artificial Intelligence / Machine Learning (AI / ML) such as Computer Vision (Image and Video Processing), Natural Language Processing (NLP), and Audio Modeling. We also bring the best ideas, tools, and approaches in technology infrastructure (AWS, DevOps, etc.) to the IC. The tech stack used is extremely broad - anything cutting edge in the commercial market, the open source community, or the academic research community is likely involved: and if something isn't being looked at yet, you can make that happen.This effort supports ALL missions of the Intelligence Community, including cyber-related data science missions. A seamless group of contractor and customer personnel work to create innovations that supply customer groups with the data sets, models, algorithms, software, and infrastructure they need to increase their mission success. Management is hands off, gives the team the freedom to explore new approaches, and markets the best ideas and results to all the other IC customers. This project regularly needs various types of people - Data Scientists, Data / ETL Engineers, Analytic Software Engineers, Full Stack Developers, UI/UX Developers, and AWS/DevOps experts. We're particularly interested in people with any of the following experience: - developing AI / ML models (neural networks, tree based algorithms, etc.); - conducting data analysis in the fields of Computer Vision, NLP, or audio signal processing; - doing data ingest and ETL into sponsor environments; or - building data-analytic software systems.Work on this program takes place throughout the Reston/Herndon/Chantilly, VA area (we cannot support remote work) and requires a TS/SCI + Poly clearance (acceptable to this customer).What You'll be OwningGRVTY is seeking a Data Scientist with a TS/SCI + Poly clearance (applicable to this customer) to join one of our top projects in Chantilly, VA. This role requires applying advanced analytics, statistical modeling, and machine learning techniques to identify, analyze, cyber related data. This role involves working closely with cyber SMEs to build AI/ML models and analytics to solve client's challenges. What You Must Have<ul><li>Active TS/SCI with Polygraph Clearance</li><li>3-5 years of experience as a Data Scientist, with a STEM degree (field such as computer science, statistics, data analytics, computer engineering, mathematics, etc.).</li><li>Programming knowledge in Python or similar language. </li><li>Experience with both Linux and Windows® Operating Systems.</li><li>Experience working with Cyber data to include examples such as (Shodan, Censys.IO, etc.). </li><li>Demonstrated experience with cleaning, managing, optimizing performance with, and processing large volumes of unstructured text data. </li></ul><div>Why Choose GRVTY<hr />The toughest national security challenges demand vision and ingenuity, not just resources. We deliver mission and technical expertise to outpace our adversaries. We're purpose-built to tackle the most entrenched, systemic national security issues around the world.We partner with our customers to help them overcome challenges in every corner of technology and defense—including the ones still being explored. Our growing capabilities create complementary advantages, giving on-the-ground operations the edge they need to succeed. We muster everything we have to answer every challenge presented, every day of our lives.At GRVTY, we believe that when our employees thrive, our company thrives. That's why we offer a comprehensive and competitive benefits package designed to support your well-being, growth, and work-life balance.• Robust health plan including medical, dental, and vision • Health Savings Account with company contribution • Annual Paid Time Off and Paid Holidays • Paid Parental Leave • 401k with generous company match • Training and Development Opportunities • Award Programs • Variety of Company Sponsored EventsEEO Statement<hr />GRVTY, is an Equal Opportunity Employer.  All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran and will not be discriminated against on the basis of disability. Anyone requiring reasonable accommodations should email recruiting@grvty.com or call 703-544-7930 with requested details.  A member of the HR team will respond to your request within 2 business days. Know Your Rights: Workplace Discrimination is Illegal (eeoc.gov)  Please review our current job openings and apply for the positions you believe may be a fit. If you are not an immediate fit, we will also keep your resume in our database for future opportunities.</div></div></div>

<h3>Job Description</h3><div>Job Description<div>Data Scientist, RNA BiologySouth San Francisco, California, United Stateswe build artificial intelligence to pioneer new frontiers in drug discovery. Our unique R&D platform, an early version of which was featured on the cover of Science, provides new strategies to treat previously undruggable diseases by targeting RNA. We continue to advance this platform by developing new machine learning methods and unique foundation models fueled by our large-scale, in-house experimental data collection. We are an interdisciplinary team of scientists and engineers and believe our people are our greatest strength and the key to our success.The opportunityAs a full-time Data Scientist on the Machine Learning team, you will work closely with scientists and engineers to apply and advance our technology platform for RNA structure prediction, target identification, and early-stage drug discovery. You will lead the curation of RNA-focused datasets for ML training and validation, discover statistical patterns in our large-scale datasets evaluating RNA structure and RNA-small molecule interactions, and devise and implement new strategies to test the accuracy of our ML models. Your analysis will guide the development of improved ML models and the targeted acquisition of new experimental data.This is a hybrid position with three days in-person at our South San Francisco office.Responsibilities:Provide RNA biology and RNA structure expertise on the ML team.Enable and apply our RNA-structure platform to prioritize RNA targets for small-molecule therapies and advance structure-based drug discovery.Generate insights from datasets on RNA structures and small molecule interactions (e.g. chemical probing, RNA-SM screens) by conducting statistical analyses, interpreting biological noise, and applying RNA domain expertise.Curate RNA datasets for training of ML models, help evaluate model performance, and provide directions for improvement.Inform scientific questions and ML model development in early-stage RNA drug discovery.Collaborate with the internal wetlab team and shape the design of experimental assays on RNA structure and RNA-SM interactions.About you:Ph.D. in Computational Biology, Bioinformatics, Statistics, Biophysics, or related field, or equivalent experience.Expertise in RNA biology and biochemistry, RNA-protein interactions, and RNA structure.Proficiency in Python for data curation and analysis at scale, and fluency with libraries for data analysis (NumPy, pandas) and applied ML (scikit-learn).Strong programming background, familiarity with Unix and comfort with using external software packages.Strong foundation in statistics and experience with conducting statistical analysis of large-scale datasets.Excellent presentation and writing skills, able to clearly communicate technical information to colleagues.Pluses:History of scientific achievement, e.g. as evidenced by publication of impactful papers.Conceptual understanding of ML model development and evaluation, and experience using ML models.Experience with computational structural biology tools for modeling RNA secondary and tertiary structure (e.g. Rosetta, AlphaFold, RNAfold).Understanding of RNA-SM interactions, including familiarity with structural properties of binding sites and experimental methods for evaluating binding.Proficiency with pipelines for next-generation sequencing dataset processing.Exposure to high throughput experimental assays for evaluating RNA structure and screening RNA-SM interactions.Salary Range: $135,000/year to $180,000/year + equity + benefits. This range reflects variations in seniority, expertise, and skills.</div></div>

About Mirakl:Founded in 2012, Mirakl has been at the forefront of marketplace innovation, empowering every business to compete in the platform economy. Today, Mirakl’s operating system combines an enterprise marketplace solution (Mirakl Platform) that enables retailers and B2B organizations to launch, scale, and operate marketplaces and dropship, AI-powered multichannel selling (Mirakl Connect), retail media (Mirakl Ads) and an agentic commerce infrastructure (Mirakl Nexus). With dual headquarters in Boston and Paris, Mirakl helps a global ecosystem of 450+ marketplaces (B2C and B2B) and a network of over 100k third-party marketplace sellers. Brands like Macy’s, Decathlon, Carrefour, Asos, and Airbus Helicopters use Mirakl to grow their businesses in new and remarkable ways.For more information: <a>www.mirakl.com</a>.Mirakl in Numbers:<ul><li>????️ Founded in 2012 | Member of French Tech Next40</li><li>???? 750+ employees in 9 offices worldwide: Paris, Barcelona, Bordeaux, Boston, London, Munich, New York, Sydney, Tokyo</li><li>???????? 350+ Mirakl Tech teams members mainly based in France</li><li>⚙️ 5 Saas Solutions</li></ul>Our Values:Working at Mirakl means accelerating your career alongside ambitious, passionate, and supportive colleagues. We're proud of the diversity of backgrounds, perspectives, and experiences that make our teams unique.Our 5 values guide how we collaborate:<ul><li>???? Work Hard Together: Teamwork and collaboration are the foundation of our success</li><li>???? Get Things Done:  We prioritize action and efficiency for impactful results</li><li>???? Go Above & Beyond:  We tackle challenges proactively and always aim for excellence</li><li>???? Succeed Through Expertise: Knowledge sharing and continuous learning are core to our culture</li><li>???? Satisfy & Empower Clients: We're committed to our clients' success</li></ul> About the jobAs part of our Data team (60+ people), your main mission will be to prototype, iterate, and put algorithms into production in collaboration with the Product teams, Data Engineers, and Development teams.The topics you will be working on will have a real impact on 450+ of the world's largest retailers (Best Buy, Decathlon, Leroy Merlin, Macy's, etc.) and 100k+ sellers. The goal is to make the most of our rich and varied data in order to increase their revenue, optimize the operational management of their businesses, and ensure the security of users and transactions. We are looking for someone as a freelance contractor, based in our offices 3 days per week in Paris or Bordeaux. Here are some of the current and future topics the team is working on:<ul><li>Detecting anomalies in product prices</li><li>Analyzing sentiment in seller/consumer exchanges to prioritize critical messages</li><li>Estimating package delivery times</li><li>Predicting and anticipating stock shortages</li><li>Detecting anomalies in seller behavior</li><li>Developing AI agents to help sellers take action on their businesses </li></ul>This job offers you: <ul><li>Implementing algorithms that will have a visible impact on more than 500 e-commerce sites/marketplaces in 40 countries, some of which are very large (millions of products, customers, orders per year)</li><li>A wide variety of techniques (time series, heuristics, deep learning, NLP, LLM, etc.)</li><li>Real autonomy and responsibility in the projects you own </li></ul>Our stack and tools: Python, Tensorflow, Keras, Pytorch, Databricks, Spark, AWS (Amazon Redshift, s3, etc.), SQL, Airflow, Delta Lake On a daily basis, you will:<ul><li>Analyze and prepare data, prototype algorithms</li><li>Put them into production in collaboration with Data Engineers and development teams</li><li>Create dashboards to illustrate the relevance of algorithms and monitor production</li><li>Present results at weekly data science meetings and participate in team brainstorming sessions</li><li>Liaise with other teams to refine use cases, user experience, and integration methods</li></ul> You will enjoy this job if:<ul><li>You have a background in machine learning, mathematics, computer science (or a related field)</li><li>You already have 3 years of experience in a similar position</li><li>You have significant experience in applied ML in a business setting</li><li>You have a good knowledge of machine learning and deep learning algorithms (particularly state-of-the-art architectures, such as Transformers)</li><li>You are proficient in Python, Tensorflow, and/or PyTorch</li><li>You are pragmatic, data-driven, and business-oriented with good team spirit</li><li>You like to take ownership of your projects and are curious</li><li>You have a positive attitude: respect and kindness are part of your values</li></ul> Want to join us? ⭐<ul><li>A 30-minute phone call with one of our Tech recruiters. This will be an opportunity to discuss your background and expectations, and to find out what Mirakl can offer you in return</li><li>An initial 30-minute technical discussion via Zoom with a member of the Data Science team, which will allow you to delve into the more specific aspects of your expertise and discover how your skills can be integrated into our projects</li><li>A practical case study to complete at home</li><li>A 75-minute technical review and discussion with a manager from the Data Science team</li><li>A final 1-hour Zoom meeting with future Mirakl colleagues to discuss our values and corporate culture. </li></ul> We welcome collaborators with their diverse perspectives and experiences to power us forward. These often far exceed conventional job requirements and help us create a culture of continuous learning. If you’re ready to join a global leader powering digital transformation for 450+ of the world’s most innovative retailers and B2B organizations..We may use Artificial Intelligence (AI) solutions to help streamline our hiring process, including screening applications, analyzing resumes, and assessing responses. While AI helps us work efficiently, all final hiring decisions are made by humans. For more information, visit our <a>AI Guidelines for Candidates and Interviews</a>.

Data ScientistLocation: BangaloreExperience: 3 – 4 YearsEmployment Type: Full-timeRole OverviewWe are looking for a skilled Data Scientist with strong expertise in machine learning, statistical analysis, and data modeling. The ideal candidate will work with large datasets to build predictive models, uncover insights, and develop AI-driven solutions that support data-driven business decisions.This role involves working closely with data engineers, software developers, and business stakeholders to design and deploy intelligent analytics solutions.Key ResponsibilitiesData Analysis & Modeling<ul><li>Analyze large and complex datasets to identify patterns, trends, and insights.</li><li>Develop statistical models and machine learning algorithms to solve business problems.</li><li>Perform exploratory data analysis to support data-driven decision-making.</li></ul>Machine Learning Development<ul><li>Design, develop, and deploy machine learning models for predictive analytics.</li><li>Implement supervised and unsupervised learning algorithms.</li><li>Evaluate model performance and optimize algorithms for accuracy and scalability.</li></ul>Data Preparation<ul><li>Perform data cleaning, preprocessing, and feature engineering.</li><li>Transform and prepare structured and unstructured datasets for model training.</li></ul>AI & Advanced AnalyticsDevelop AI-driven solutions such as:<ul><li>Predictive analytics models</li><li>Recommendation systems</li><li>Forecasting models</li><li>Anomaly detection systems</li></ul>Model Deployment<ul><li>Deploy machine learning models into production environments.</li><li>Work with engineering teams to integrate models into applications and platforms.</li><li>Monitor and improve model performance post-deployment.</li></ul>Collaboration<ul><li>Work closely with Data Engineers, Software Engineers, and Product teams.</li><li>Translate business requirements into data science and machine learning solutions.</li></ul>Required SkillsProgramming<ul><li>Python</li><li>SQL</li></ul>Data Science & ML Libraries<ul><li>Pandas</li><li>NumPy</li><li>Scikit-learn</li><li>TensorFlow / PyTorch</li></ul>Machine Learning<ul><li>Regression</li><li>Classification</li><li>Clustering</li><li>Model evaluation and validation techniques</li></ul>Data Visualization<ul><li>Power BI</li><li>Tableau</li><li>Matplotlib</li><li>Seaborn</li></ul>Data Platforms<ul><li>Experience working with large datasets and data pipelines.</li></ul>Preferred Skills<ul><li>Experience with Cloud platforms (AWS, Azure, or GCP)</li><li>Knowledge of Deep Learning frameworks</li><li>Experience with NLP or Generative AI models</li><li>Familiarity with Big Data technologies such as Apache Spark</li></ul>Qualifications<ul><li>Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field</li><li>3–4 years of experience in Data Science, Machine Learning, or Advanced Analytics</li></ul>Success Metrics<ul><li>Accuracy and performance of machine learning models</li><li>Business insights generated through data analysis</li><li>Successful deployment of ML/AI models into production</li><li>Contribution to data-driven decision-making</li></ul>

Calculate Moving Average	SQL	Easy
Predict Customer Churn	Machine Learning	Medium
A/B Test Significance	Statistics	Medium
Optimize Query Performance	SQL	Hard
Feature Importance Analysis	Machine Learning	Medium
Clean Missing Data	Python	Easy
Neural Network Architecture	Deep Learning	Hard
Calculate Cohort Retention	SQL	Medium
Bayesian Probability	Statistics	Easy
Recommend Similar Products	Machine Learning	Hard

H-E-B Data Scientist Interview Questions + Guide in 2025

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