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

Epic! Data Scientist Interview Guide

Getting ready for an Data Scientist interview at Epic!? The Epic! Data Scientist interview span across 10 to 12 different question topics. In preparing for the interview:
<ul>
<li>Know what skills are necessary for Epic! Data Scientist roles.</li>
<li>Gain insights into the Data Scientist interview process at Epic!.</li>
<li>Practice real Epic! 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 Epic! Data Scientist interview.


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

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

Overview

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.

Epic! Data Scientist Interview Process

Let’s say that you’re working on a job recommendation engine. You have access to all user Linkedin profiles, a list of jobs each user applied to, and answers to questions that the user filled in about their job search.

Using this information, how would you build a job recommendation feed?

What problem can arise in job recommendation systems with regard to initial recommendations?

What problem can arise in job recommendation systems with regard to initial recommendations?

Job Recommendation

Given a list of integers, find the index at which the sum of the left half of the list is equal to the right half. If there is no index where this condition is satisfied return -1.

Note: the number that lies on the index is calculated to the left side of the list.

Example 1:

Input:

<pre tabindex="0" class="chroma"><code>nums = [1, 7, 3, 5, 6]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>equivalent_index(nums) -&gt; 2
</code></pre>

In this example, the sum of the elements to the left of index 2 (1 + 7) is equal to the sum of the elements to the right of index 2 (5 + 6).

Example 2:

Input:

<pre tabindex="0" class="chroma"><code>nums = [1,3,5]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>equivalent_index(nums) -&gt; -1
</code></pre>

In this example, there is no index where the sum of the elements to the left is equal to the sum of the elements to the right.

The task is to write a function that takes a list of integers as input and returns the index at which the sum of the integers to the left of the index is equal to the sum of the integers to the right. If no such index exists, the function should return -1.

Find the Index with Equal Left and Right Sum

Let’s say you are designing a marketplace for your website.

Selling firearms is prohibited by your website’s Terms of Service Agreement (not to mention the laws of your country). To this end, you want to create a system that can automatically detect if a listing on the marketplace is selling a gun.

How would you go about doing this?

While designing a system to detect firearms listings on a marketplace website, what metrics could be used to minimize both false positives and false negatives?

While designing a system to detect firearms listings on a marketplace website, what metrics could be used to minimize both false positives and false negatives?

Detecting Firearm Sales

How would you build a model to detect if a post on a marketplace is talking about selling a gun?

Epic! Data Scientist Interview Questions

Sr. Principal Data Scientist / Machine Learning Engineer  Ascentt is building cutting-edge data analytics & AI/ML solutions for global automotive and manufacturing leaders. We turn enterprise data into real-time decisions using advanced machine learning and GenAI. Our team solves hard engineering problems at scale, with real-world industry impact. We’re hiring passionate builders to shape the future of industrial intelligence.
Job Summary
We're looking for an exceptionally skilled and experienced Sr. Principal Data Scientist / Machine Learning Engineer to lead and deliver high-impact AI/ML projects across Automotive domain. The ideal candidate will have a deep understanding of data science and machine learning tools, techniques, and algorithms, coupled with a proven track record of successfully leading projects from conception to deployment. This role demands strong client-facing communication skills and the ability to translate complex technical concepts into tangible business value.
Key Responsibilities
Technical Leadership & Strategy:
Serve as a primary technical expert and thought leader in Data Science and Machine Learning.
Define and drive the technical strategy for AI/ML initiatives, identifying high-value opportunities for optimization, predictive analytics, and process improvement across diverse use cases.
Architect and oversee the development of robust, scalable, and production-ready DS/ML models and solutions.
Stay at the forefront of the latest advancements in DS/ML, especially those applicable to various industries and large-scale data problems.
Lead end-to-end DS/ML projects, including requirements gathering, data exploration, model development, validation, deployment, and monitoring.
Define project scope, timelines, and deliverables, ensuring successful execution within budget and schedule constraints.
Mentor and guide junior and mid-level data scientists and ML engineers, fostering a culture of technical excellence and continuous learning.
Drive MLOps best practices for reliable and efficient model deployment and lifecycle management.
Client Management & Communication:
Act as a trusted advisor to clients and internal stakeholders, understanding their business challenges and translating them into solvable DS/ML problems.
Effectively communicate complex analytical findings, model performance, and business recommendations to both technical and non-technical audiences.
Manage client expectations, present progress reports, and ensure stakeholder satisfaction.
Facilitate workshops and discovery sessions to identify new opportunities for AI/ML adoption.
Use Case Development & Problem Solving:
Lead the identification, prioritization, and execution of complex AI/ML use cases that drive significant business impact.
Apply deep analytical skills to dissect complex problems, derive actionable insights from data, and design innovative solutions.
Develop and implement models for:
Predictive Analytics: Forecasting, risk assessment, and anomaly detection.
Optimization: Improving efficiency, resource allocation, and decision-making.
Pattern Recognition: Identifying trends, segments, and relationships within large datasets.
Automation: Leveraging ML for intelligent process automation and enhanced operational efficiency.
Tool & Algorithm Proficiency:
Demonstrated expertise in a wide range of DS/ML tools and platforms (e.g., Python, R, TensorFlow, PyTorch, scikit-learn, Spark, AWS Sagemaker, Azure ML).
Deep understanding and practical application of various machine learning algorithms (e.g., supervised, unsupervised, reinforcement learning, deep learning, time series analysis, NLP, computer vision).
Proficiency in data manipulation, SQL, and working with large, complex datasets from various sources.
Qualifications
Master's or Ph.D. in Data Science, Machine Learning, Computer Science, Engineering, Operations Research, Statistics, or a related quantitative field.
8+ years of progressive experience in Data Science and Machine Learning roles, with at least 3-5 years in a leadership or principal-level capacity.
Demonstrated experience leading multiple end-to-end DS/ML projects successfully from concept to production.
Proven track record of managing client interactions, presenting technical solutions, and influencing strategic decisions.
Expertise in Python programming (NumPy, Pandas, Scikit-learn, Keras/TensorFlow/PyTorch).
Strong understanding of statistical modeling, experimental design, and hypothesis testing.
Experience with cloud platforms (AWS, Azure, GCP) and MLOps principles.
Excellent communication, interpersonal, and presentation skills.
Preferred Qualifications
Experience with real-time data processing and streaming analytics.
Knowledge of various industry verticals and their unique data challenges (e.g., finance, healthcare, retail, logistics, manufacturing).
Experience with large-scale data architectures (e.g., data lakes, data warehouses, distributed computing).
Publications or presentations in relevant fields.

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Senior Data Scientist Manager, Product, Play Games  Join to apply for the  Senior Data Scientist Manager, Product, Play Games  role at  Google
Senior Data Scientist Manager, Product, Play Games  1 week ago Be among the first 25 applicants
Join to apply for the  Senior Data Scientist Manager, Product, Play Games  role at  Google
Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
13 years of experience with analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) or 10 years of experience with Master's degree.
5 years of experience as a people manager within a technical leadership role.

Minimum qualifications:

Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
13 years of experience with analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) or 10 years of experience with Master's degree.
5 years of experience as a people manager within a technical leadership role.

Preferred qualifications:

Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
15 years of experience with analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).
6 years of experience as a people manager within a technical leadership role.

About the job Help serve Google's worldwide user base of more than a billion people. Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, you serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. You'll make critical recommendations for your fellow Googlers in Engineering and Product Management. You relish tallying up the numbers one minute and communicating your findings to a team leader the next.

The Play Games team’s serve as the go-to-platform for gaming, for users and developers, across the lifecycle of titles, from development to growth.

In this role, you will lead a team of Data Scientists located in the United States, United Kingdom, and India in providing insights that help Product and Go-To-Market (GTM) teams take the decisions to delight users, grow business, and deliver Return on Investment for developer partners.Google is an engineering company at heart. We hire people with a broad set of technical skills who are ready to take on some of technology's greatest challenges and make an impact on users around the world. At Google, engineers not only revolutionize search, they routinely work on scalability and storage solutions, large-scale applications and entirely new platforms for developers around the world. From Google Ads to Chrome, Android to YouTube, social to local, Google engineers are changing the world one technological achievement after another.

The US base salary range for this full-time position is $227,000-$320,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google .

Responsibilities

Perform analysis utilizing related tools (e.g., SQL, R, Python). Direct projects that combine investigative and organizational tests towards decisions.
Own end-to-end projects, covering problem definition, metrics development, data extraction and manipulation, visualization, creation, and implementation of investigative/statistical models, and presentation to stakeholders.
Oversee the integration of cross-functional/organizational project/process timelines, drive improvements and recommendations, and define operational goals and objectives.
Identify key areas for the team based on goals of the Games business and its Loyalty program. Distill these areas into projects, and obtain buy-in for them from the stakeholders.
Mentor and manage junior data scientists, promote a culture of technical excellence and learning within the team.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form . Seniority level    Seniority level Mid-Senior level
Employment type    Employment type Full-time
Job function    Job function Information Technology and Engineering
Industries Information Services and Technology, Information and Internet
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At Webflow, our mission is to bring development superpowers to everyone. As the pioneer of the Website Experience Platform (WXP), we’re redefining how teams Build, Manage, and Optimize for the web — combining visual development, powerful content management systems, AI-driven personalization, seamless hosting, and end-to-end analytics in a single, unified platform. With AI at the core, Webflow helps teams move faster, create more performant digital experiences, and scale without heavy engineering support. From independent designers and creative agencies to global enterprises, hundreds of thousands of organizations use Webflow to turn ideas into reality — and to power what’s possible on the web.
We’re adding a Staff Data Scientist to our team to help inform the future of Webflow with data by building a deep understanding of how our customers create for the web with our product. You’ll partner directly with key product stakeholders to identify interesting business questions and provide the data and quantitative analysis to answer them, leading the development of KPIs and helping teams understand how to improve our user experience.
About the role:    Location: Remote-first (United States; BC & ON, Canada)
Full-time
Permanent
Exempt
Our cash compensation amount for this role ranges depending on the cost of labor of the geographic area. The ranges shared below may change if you are hired in another geographic location.  United States (all figures cited below in USD and pertain to workers in the United States)  Zone A: [$175,000 - $247,000
Zone B: [$164,000 - $232,000]
Zone C: [$154,000 - $217,000]

Canada (All figures cited below in CAD and pertain to workers in ON & BC, Canada)  [$199,000 - $281,000]

This role is also eligible to participate in Webflow's company-wide bonus program. Target amounts are a percentage of base salary and vary by career level. Payouts are based on company performance against established financial and operational goals.
Please visit our Careers page for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter.
Reporting to the VP of Data & Insights
As a Staff Data Scientist, you’ll:
Lead high-impact projects to drive insights and decision-making across Webflow’s most critical initiatives.
Define and evolve product and business metrics in collaboration with cross-functional teams to measure user experience and product performance
Advance our experimentation capabilities, guiding design, statistical analysis, and interpretation of A/B tests, and championing a rigorous, iterative approach to product development.
Uncover growth opportunities through exploratory data analyses, customer segmentation, and predictive modeling that surface actionable insights across the customer journey.
Lead technical and non-technical team members with processes and technical expertise for executing experiments, answering open ended business questions with data, and researching levers for improving our product
Partner with stakeholders in Product, Engineering, Design, Marketing, and User Research to blend qualitative and quantitative insights, informing product direction and enhancing user experience.
Develop our data foundation collaborating on our strategic roadmap for building new pipelines and tools that contribute to our connected, complete understanding of our customer journey and improve our customer experience.
In addition to the responsibilities outlined above, at Webflow we will support you in identifying where your interests and development opportunities lie and we'll help you incorporate them into your role.
About you:   You’ll thrive as a Staff Data Scientist if you:
Have 5+ years of experience  in a Data Science (or similar) position
Have interest and experience  in mentoring and developing the technical skills of your team members, helping to build a collaborative data science practice
Have demonstrated experience  working as a Data Scientist (or the equivalent in quantitative analysis), contributing to the strategic roadmap, providing high quality, reproducible analysis that impacts company strategy and decision making, building tools to enable scalable processes and enabling others to do the same
Have expertise  in applied statistics (e.g. predictive modeling, hypothesis testing, regressions), segmentation and experimentation (e.g. A/B testing) in an industry setting and the ability to explain concepts to technical and non-technical team members
Have   proficiency  in SQL, and experience with a programming language like Python or R
Curious  about diving into the nuances of our business and product data
Thrive collaborating  with product teams in a fast-paced and sometimes ambiguous environment, solving complex and nuanced problems
Engage both technical and nontechnical audiences with clear and compelling communication
Stay curious and open to growth  — actively building fluency in emerging technologies like AI to unlock creativity, accelerate progress, and amplify impact.
Our Core Behaviors:     Obsess over customer experience.  We deeply understand  what  we’re building and  who  we’re building for and serving. We define the leading edge of what’s possible in our industry and deliver the future for our customers
Move with heartfelt urgency.  We have a healthy relationship with impatience, channeling it thoughtfully to show up better and faster for our customers and for each other. Time is the most limited thing we have, and we make the most of every moment
Say the hard thing with care.  Our best work often comes from intelligent debate, critique, and even difficult conversations. We speak our minds and don’t sugarcoat things — and we do so with respect, maturity, and care
Make your mark.  We seek out new and unique ways to create meaningful impact, and we champion the same from our colleagues. We work as a  team  to get the job done, and we go out of our way to celebrate and reward those going above and beyond for our customers and our teammates
Benefits & wellness    Equity ownership (RSUs) in a growing, privately-owned company
100% employer-paid healthcare, vision, and dental insurance coverage for full-time employees (working 30+ hours per week) and their dependents. Full-time employees may also be eligible for voluntary insurance options where applicable in the respective country of employment
12 weeks of paid parental leave for both birthing and non-birthing caregivers, as well as an additional 6-8 weeks of pregnancy disability leave for birthing parents to be used before child bonding leave (note: where local requirements are more generous, employees receive the greater benefit); full-time employees also have access to family planning care and reimbursement
Flexible PTO for all locations and sabbatical program
Access to mental wellness and professional coaching, therapy, and Employee Assistance Program
Monthly stipends to support work and wellness
401k plan or pension schemes (in countries where statutorily required), and other financial wellness benefits, like CPA and financial advisor coverage
Temporary employees may be eligible for paid holiday and time off, statutory leaves of absence, and company-sponsored medical benefits depending on their Fixed Term Contract and their country/state of employment.
Remote, together   At Webflow, equality is a core tenet of our culture. We are an Equal Opportunity (EEO)/Veterans/Disabled Employer and are committed to building an inclusive global team that represents a variety of backgrounds, perspectives, beliefs, and experiences. Employment decisions are made on the basis of job-related criteria without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other classification protected by applicable law. Pursuant to the San Francisco Fair Chance Ordinance, Webflow will consider for employment qualified applicants with arrest and conviction records.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Upon interview scheduling, instructions for confidential accommodation requests will be administered.
To join Webflow, you'll need a valid right to work authorization depending on the country of employment.
If you are extended an offer, that offer may be contingent upon your successful completion of a background check, which will be conducted in accordance with applicable laws. We may obtain one or more background screening reports about you, solely for employment purposes.
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3 Openings (Data Engineer, Data Scientist, Data Analyst)Location: Hybrid (2-3 days a week onsite), Denver CO Pay Rate: $70 - $80 /hr. on W2 with benefitsContract: Long Term Contract (possibility of conversion to an FTE) SummaryThe Data Science team is a high-performing group charged with developing analytics solutions for product owners across the company. As part of this group, you will play a pivotal role in supporting a brand new "closed loop" initiative, which involves leveraging NLP and LLM within AI to enhance an outage management tool. Responsibilities include developing and deploying analytical models to detect network outages,processing real- time data, and implementing monitoring and testing for production jobs. Additionally, this role will serve as a liaison between the Data Science and the MLOps team to implement machine learning pipelines and ensure seamless integration. Responsibilities <ul><li>Develop and maintain machine learning models for network outage detection and classification.</li><li>Build models using NLP, LLM, classification, and regression techniques.</li><li>Work on feature engineering and model optimization.</li><li>Analyze and interpret model outputs to provide actionable business insights.</li><li>Collaborate with data engineers to operationalize models in cloud environments.</li><li>Support business intelligence by meeting with stakeholders and refining models.</li><li>Conduct data exploration, feature selection, and high-level ML approaches.</li></ul>Required Qualifications <ul><li>Proficiency in Python or R for modeling and analysis.</li><li>Experience with ML libraries: Scikit-learn, Pandas, XGBoost, Jupyter Notebooks/Labs.</li><li>Strong understanding of classification and regression models.</li><li>Ability to ask the right questions and refine models based on real-world data.</li><li>Comfortable with high-level data analytics and feature importance interpretation.</li></ul>Preferred Qualifications <ul><li>Knowledge of cloud ML services (AWS SageMaker, GCP AI Platform).</li><li>Experience with NLP and LLM for AI-driven analytics.</li><li>Understanding of model deployment and MLOps practices.</li></ul>

Bear Cognition is a Software with a Service (SwaS®) company that combines AI-powered technology with expert consulting to help organizations turn complex data into actionable intelligence. We specialize in AI-enhanced analytics, workflow optimization, and intelligent automation. Our “problem-first, tech-second” approach ensures every solution is tailored to fit the unique business challenges of our clients, delivering faster insights and smarter decisions at scale. Job Summary The primary focus of this position will be to develop and deploy Machine Learning Algorithms on client data to provide business insights that will then be communicated in the form of data visualization. The Data Scientist is responsible for data preparation, the ML development cycle, and creating documentation around best practices when it comes to machine learning models. The position may involve direct contact with customers, business consultants, and company executives. *Bear Cognition runs a hybrid schedule and would require this hire to live in or relocate to the Charleston, SC area. *Bear Cognition does NOT offer visa sponsorships. Duties/Responsibilities <ul><li>Responsible for products that are accurate, efficient, and well documented. </li><li>Design, architect and build AI/ML solutions. Including the training, testing, deployment, and monitoring of machine learning models in production. </li><li>Develop Agentic AI orchestration pipelines using the lates Generative AI solutions. </li><li>Work hands on across the stack, from architecture and data ingestion to model development and UX integration. </li><li>Works collaboratively with peers to develop quality processes, frameworks and products per agreed timelines. </li><li>Identify business obstacles (through analysis) and produce actionable solutions. </li><li>Exceptional communication skills and ability to work with management at every level </li><li>Provides detailed analysis of customer data that can easily be translated into visual representations. </li><li>Acts as the first line of support for data questions and issues. </li><li>Identify new research topics that have relevancy and value add to our projects. </li></ul> Requirements <ul><li>Minimum of 3 years of data science experience </li><li>Bachelor's degree in Data Science, Statistics, or a related field, or 3 additional years of relevant work experience </li><li>Strong fluency in Python and SQL </li><li>Strong Experience with Developing and Deploying Machine Learning Models using Python or other coding language, while leveraging ML tools such as Pandas, Scikit-learn, and MLflow </li><li>Strong ability to communicate ML model results to peers and to visualizations for non-technical stakeholders </li><li>Experience with GenAI applications, including RAG, agents, Text2SQL </li><li>Familiarity with LangChain, LangGraph and deploying LLM’s </li><li>Strong mathematical knowledge (Queueing Theory, Linear Programming, Game Theory, Probability, Poisson Distributions, etc.) </li><li>Advanced in Statistical Analysis </li><li>Ability to create advanced formulas and dynamic dashboards </li><li>Strong organizational skills, able to deliver within fixed deadlines </li><li>Demonstrates a collaborative mindset and a commitment to continuous learning </li><li>Strong analytical skills, user interface design skills, work ethic, critical thinking, problem solving ability, effective communication skills, and overall positive attitude </li></ul> Preferred <ul><li>Experience with developing machine learning models for clients </li><li>Experience with Generative AI solutions </li><li>Experience with Snowflake </li><li>Experience with Amazon Web Services (AWS) services such as SageMaker and Bedrock </li><li>Knowledge the machine learning lifecycle and MLOps best practices </li><li>Experience with Flask, FastAPI and web application frameworks </li></ul> Please visit our website to learn more about Bear Cognition at www.bearcognition.com. Bear Cognition is an Equal Opportunity Employer. Bear Cognition strives to make employment decisions on the basis of merit, seeking the most qualified individuals in every job. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, pregnancy, gender identity or expression, sexual orientation, marital status, national origin or ancestry, genetics, disability, age, veteran status, or other status protected by law. All employment decisions will be based on valid job requirements or other legitimate, non-discriminatory reasons. Bear Cognition offers reasonable accommodations for individuals with disabilities in the job application and hiring process. If you would like to request such an accommodation, please contact the Vice President of Human Resources for Bear Cognition.

Role: Technical lead – Data ScientistLocation: Berkeley Heights, NJ Mode Of Hire: Full Time Roles and Responsibilities:<ul><li>Lead a team of Data Scientists, ML Engineers, Data Engineers, and QA in liaison with client stakeholders to produce end-to-end pipelines that deliver business value to client.</li><li>Utilize data analytics tools and methodologies to conduct in-depth assessments and generate Fraud rules and reports on fraud trends (including Merchant Fraud, first party and third-party fraud).</li><li>Investigate suspicious activities and transactions, determine root causes and develop strategies and statistical models to prevent future occurrences.</li><li>Translate business requirements of client into definitive AI/ML solutions and assign specific roles to each team member.</li></ul> Skills Required:<ul><li>12+ years of experience in fraud analytics, risk management, or financial crime analytics in the banking sector with an additional emphasis on transaction monitoring</li><li>Machine Learning and Business Articulation</li><li>Expertise: Extensive experience in designing, developing, and deploying machine learning models to detect and mitigate fraud. Candidate should demonstrate a high degree of capability to translate client business statements/briefs into data-driven solutions.</li><li>Fintech & Fraud Detection: Background in the Fintech industry, with specific experience in financial crime and fraud detection, applying data science to solve real-world business problems.</li><li>Advanced Tools and Platforms: Experience with tools such as PySpark, Databricks, AWS, or GCP for processing large datasets, training models, and deploying them at scale.</li><li>Candidate must demonstrate following in their experience</li><li>SME level expertise on Fraud Patterns and associated solutions</li><li>Thorough knowledge of AWS ecosystem in context of AI/ML solutions</li><li>Understanding Model Risk Management requirements as part of solution</li><li>Excellent command of PowerPoint for creating apt business presentations</li><li>Expertise in AI / ML with strong focus on leveraging cloud platforms like AWS to build scalable, production-grade applications.</li><li>Strong experience with advanced SQL and good to have experience in Pyspark.</li><li>Good understanding or experience of working in AWS.</li><li>Proven track record of leading cross-functional teams to create state-of-the-art AI/ML artefacts.</li><li>Excellent written and verbal communication skills.</li><li>Strong understanding of fraud patterns and digital transaction behaviors.</li></ul>

UniAthena is an ed-tech, offering free-learning upskilling courses and Self-Paced Academic Programs in collaboration with European Universities and Awarding Bodies. Over 2.5 Million learners from across 150 countries are pursuing their upskilling journey on the 100% Online, self-paced and 100% automated learning platform. Job Requirement :<ul><li>3-5 Years of experience in Data Science</li><li>Strong expertise in statistical modeling, machine learning, deep learning, data warehousing, ETL, and reporting tools.</li><li>Bachelors/Masters in Data Science, Statistics, Computer Science, Business Intelligence,</li><li>Experience with relevant programming languages and tools such as Python, R, SQL, Spark, Tableau, Power BI.</li><li>Experience with machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn</li><li>Ability to think strategically and translate data insights into actionable business recommendations.</li><li>Excellent problem-solving and analytical skills</li><li>Adability and openesss towards changing environment and nature of work</li><li>This is a startup environment with evolving systems and procedures, the ideal candidate will be comfortable working in a fast-paced, dynamic environment and will have a strong desire to make a significant impact on the business.</li></ul>Job Roles & Responsibilities:<ul><li>Conduct in-depth analysis of large-scale datasets to uncover insights and trends.</li><li>Build and deploy predictive and prescriptive machine learning models for various applications.</li><li>Design and execute A/B tests to evaluate the effectiveness of different strategies.</li><li>Collaborate with product managers, engineers, and other stakeholders to drive data-driven decision-making.</li><li>Stay up-to-date with the latest advancements in data science and machine learning.</li></ul>

As a Senior Data Scientist, you will play a key role in empowering consumers and creating business value by designing, developing, and deploying intelligent solutions across a diverse range of clients including Financial Institutions, FinTechs, SMEs, Large Enterprises, and Government Agencies. You will focus on delivering "Certainty as a Service" through explainable and trustworthy models in domains such as lending, financial decisioning, management, and payments. Key Responsibilities: <ul><li>Design, develop, and deploy advanced machine learning and deep learning models for production use.</li><li>Create consumable metrics, explainability frameworks, and confidence measures for decision-making solutions.</li><li>Drive insights from complex and diverse datasets, including structured, unstructured, and time-series data.</li><li>Work across Verification Services, Entity Resolution, Attribute & Temporal Analysis, and related platforms.</li><li>Perform advanced error analysis, dimensionality reduction, and model interpretability assessments.</li><li>Translate business problems into data science solutions in lending, credit scoring, and financial management.</li><li>Collaborate with cross-functional teams to ensure successful deployment via Kubernetes, Docker, APIs, and event-driven architecture.</li><li>Communicate findings clearly with both technical and non-technical stakeholders.</li></ul> Required Qualifications: <ul><li>Master’s Degree or higher in Data Science, Computer Science, Information Systems, or a closely related field. A Ph.D. is preferred.</li><li>10+ years of commercial experience in Machine Learning / Deep Learning, including model development and deployment.</li><li>Strong experience in Python for data science and software development.</li></ul>Solid foundation in:<ul><li>Natural Language Understanding (NLU).</li><li>Computer Vision.</li><li>Statistical Modeling</li><li>Data Visualization.</li><li>Classical and Advanced ML methods.</li><li>Experience in model interpretability and explainability.</li><li>Demonstrated ability to solve novel problems in the financial domain.</li><li>Strong experience with Kubernetes, Docker, REST APIs, GraphQL, and event streaming.</li><li>Excellent written and verbal communication skills.</li></ul> Preferred Qualifications:<ul><li>Exposure to credit risk modeling, risk evaluation, and financial decision systems.</li><li>Experience in Finance or FinTech domains.</li><li>Expertise in discrete, differential, deterministic, and probabilistic mathematical modeling.</li><li>Advanced skills in Transformer models, Attention Mechanisms, PCA or other dimensionality reduction techniques.</li><li>Strong background in Data Architecture, Query Optimization, and ML Ops.</li><li>Familiarity with positive attribution techniques, decision science in lending, and attribute analysis.</li></ul>

As a Data Scientist at Blu Omega, you will provide end-to-end analytic support for mission operations and intelligence, from requirements gathering to model development and insight communication. You'll work with cross-functional teams to identify data sources, configure environments, and create tailored analytic products. Strong communication skills are essential for collaborating with technical teams and conveying insights to nontechnical audiences. Your work should distill trends, highlight patterns, and present actionable insights clearly and concisely. Qualifications:<ul><li>Experience in executing data science methods using python libraries for Data Cleaning/Wrangling, Exploratory Data Analysis (EDA), Statistical Analysis, and Data Visualization.</li><li>Design and implement robust model evaluation techniques to assess performance, bias, and interpretability.</li><li>Strong proficiency in programming languages such as Python.</li><li>Demonstrated knowledge of cloud architecture and data services including Lambda, Redshift, and CloudWatch for data analytics applications</li><li>Agile development experience along with related technologies (e.g., Jira).</li><li>Familiarity and experience with the Intelligence Community (IC) and Department of Homeland Security (DHS) environments and operations.</li></ul> Role Requirements:<ul><li>Minimum education requirements: Bachelor’s Degree.</li><li>Years of Experience: Bachelor's degree with 4+ years of relevant experience, or a Master's degree with 2+ years of relevant experience.</li><li>Candidates must possess an active TS/SCI clearance.</li><li>Flexibility option: High Co-Location (3-days on-site Washington, DC).</li><li>Skills: Data Analytics, Data Science, Data Visualization, AWS, Machine Learning, GitLab, Jupyter Notebooks, Python, and R Studio.</li></ul> Salary Range: $110,000-$155,000Your final salary offer will be based on several factors, including depth of technical skills, work experience, education, certifications, and clearance. What Blu Omega Can Offer You:<ul><li>Competitive benefits including Health Insurance, 401K w/ match, Paid Time Off and more.</li><li>Results driven culture that embrace our core values</li><li>Rewarding work contributing to our Nation’s mission critical programs</li></ul>Blu Omega is a Woman Owned Small Business Federal Technology services firm headquartered in Washington DC and supporting clients nationally. We provide Technology solutions for enterprise and government customers. Our team has a past performance in a diverse range of programs including those for Data Management, Cloud/Infrastructure, Software Development and Enterprise Applications. 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, or protected veteran status and will not be discriminated against on the basis of disability.

We're looking for a highly skilled Data Scientist with deep experience in image processing, digital pathology, and machine learning to join a cutting-edge project focused on advancing healthcare innovation. If you have 7+ years of experience in Python, data modeling, algorithm development, and working with large-scale datasets, this could be a great fit. Job Title: Data ScientistJob Location: Tucson, AZDuration: 12 months with possible chance of extension Key Responsibilities:<ul><li>Work closely with the Tucson-based assay and algorithm development teams to ensure seamless data integration and maintain data integrity across complex digital pathology projects.</li><li>Design, develop, and implement robust solutions to automate manual steps within the algorithm development and data management workflows, enhancing efficiency and reproducibility.</li><li>Perform sophisticated image processing, data analysis, and predictive modeling using large-scale digital pathology datasets.</li><li>Build, test, and deploy computational tools and algorithms, primarily using Python or similar languages, adhering to high standards of code quality, efficiency, and maintainability.</li><li>Leverage your skills in digital pathology, machine learning (ML), artificial intelligence (AI), and GUI development to create impactful solutions and improve algorithm performance.</li><li>Meticulously maintain the traceability and integrity of all data, including images and associated metadata, ensuring compliance with relevant standards and supporting contractual obligations.</li></ul>Minimum Qualifications:<ul><li>Bachelor’s degree in Computer Science, Data Science, Engineering, Statistics, or a related quantitative field with 7+ years of relevant experience.</li><li>Proven experience developing, testing, and deploying solutions using Python or similar programming languages within a software development lifecycle.</li><li>Solid understanding and practical experience in image analysis, machine learning/deep learning techniques, and AI concepts.</li><li>Demonstrated ability to perform complex data modeling, processing, and analysis on large or intricate datasets.</li><li>Experience developing graphical user interface (GUI) for technical applications or data visualization.</li><li>Excellent analytical and problem-solving skills with meticulous attention to detail.</li><li>Strong verbal and written communication skills, enabling effective collaboration within cross-functional teams.</li></ul>Preferred Qualifications:<ul><li>Experience working within digital pathology or imaging data environments.</li><li>Familiarity with regulatory requirements and compliance standards applicable to software as a medical device (SaMD) (e.g., FDA guidance, IVDR).</li><li>Proficiency with cloud computing platforms (e.g., AWS, Azure, GCP) and associated services.</li><li>Experience utilizing High-Performance Computing (HPC) environments for computationally intensive tasks.</li><li>Knowledge of bioinformatics or molecular modeling techniques.</li></ul>

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