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California academy of sciences Interview Questions

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Machine Learning

How would you encode a categorical variable with thousands of distinct values

Encoding Categorical Features

Interpret coefficients of logistic regression for categorical and boolean variables

Coefficients of Logistic Regression

What metrics would you use to track accuracy and validity of the model

Spam Classifier 

Explain the key differences between classification models and regression models

Classification and Regression

Bias variance tradeoff and class imbalance in finance

Bias - Variance Tradeoff and Class Imbalance in Finance

Behavioral

Strategically resolving misaligned expectations with stakeholders for a successful project outcome

Stakeholder Communication

Describing a data project and its challenges

Hurdles In Data Projects

How would you prepare and monitor a churn model before and after production deployment?

Model Deployment Pipeline

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

Why Do You Want to Work With Us

Making data-driven insights actionable for those without technical expertise

Simple Explanations

Statistics

Explain what a p-value is to someone who is not technical

P-value to a Layman

What are the assumptions of linear regression?

Assumptions of Linear Regression

What is the downside of only using the R-Squared (R^2) value to determine a relationship between two variables

Using R Squared

How would you tackle multicollinearity in multiple linear regression

Multicollinearity in Regression

Determine whether using an 83% cutoff overestimates or underestimates the actual population’s credit score

Credit Score Estimation

Product Sense & Metrics

How would you measure the success of Linkedin’s newsfeed ranking algorithm and approach conflicting success metrics

Ranking Metrics

The role of A/B testing in measuring the success rate of an analytics experiment

Success Measurement

Vision Setting and Execution Strategy

Data Pipelines

Design a scalable ETL pipeline for ingesting heterogeneous data from Skyscanner's partners.

Skyscanner Partner ETL

Design a reporting pipeline for a major tech company using only open-source tools under strict budget constraints.

Open Source Reporting Pipeline

Let’s say you have a categorical variable with thousands of distinct values, how would you encode it?

Which method can be used to extract communities from large networks, that does not require a pre-determined number of clusters like K-means?

Which method can be used to extract communities from large networks, that does not require a pre-determined number of clusters like K-means?

Tell me about a data project that didn’t go the way you expected. What did you set out to do, what surprised you, and how did you handle it?

How would you explain what a p-value is to someone who is not technical?

What does a p-value in a statistical test represent?

What does a p-value in a statistical test represent?

P-value to a Layman I

In a statistical test, how does a low p-value (less than 0.05) influence our decision about the null hypothesis?

In a statistical test, how does a low p-value (less than 0.05) influence our decision about the null hypothesis?

P-value to a Layman II

Say you are tasked with analyzing how well a model fits the data given. You want to determine a relationship between two variables.

What is the downside of only using the R-Squared $(R^2)$ value to do so?

In the context of regression analysis, why is it misleading to rely solely on a high R-squared ($R^2$) value to infer a causal relationship between variables?

In the context of regression analysis, why is it misleading to rely solely on a high R-squared ($R^2$) value to infer a causal relationship between variables?

Using R Squared I

Which of the following best describes the R-squared ($R^2$) value in the context of a regression model?

Which of the following best describes the R-squared ($R^2$) value in the context of a regression model?

Using R Squared II

What is a limitation of using R-squared ($R^2$) as the only metric to evaluate a regression model's fit?

What is a limitation of using R-squared ($R^2$) as the only metric to evaluate a regression model's fit?

Using R Squared III

You’re a data scientist at YouTube. Leadership wants to revisit how the platform measures success, not for a specific new feature, but for the product as a whole given its current state.

How would you define and measure success for YouTube? Identify your primary and secondary metrics, explain your rationale for each, and discuss how you would choose the right thresholds for any engagement-based metrics you propose.

You work as a data engineer at Skyscanner. Your team is responsible for ingesting, transforming, and loading flight and hotel availability data from dozens of external partner APIs into Skyscanner’s real-time search platform. The system must ensure high data freshness, fault tolerance, and scalability as new partners are onboarded.

How would you architect the ETL pipeline to support these requirements? Design a system flow explaining this architecture.

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

How would you interpret coefficients of logistic regression for categorical and boolean variables?

Why is one-hot encoding recommended for categorical variables in logistic regression models?

Why is one-hot encoding recommended for categorical variables in logistic regression models?

Let’s say you are tasked with building a spam classifier for emails. Assume that you’ve built a V1 of the model.

What metrics would you use to track accuracy and validity of the model?

You’ve been tasked with building a classification machine-learning model to predict whether a transaction is either fraud or not fraud for a credit card company. You have ten years of historical data on transactions, including a flag for whether a transaction was manually identified as fraud.

Describe how you might go about building a fraud detection model for credit card transactions. Be sure to mention the possible model types, discuss the bias-variance tradeoff in model development, and address any complexities that arise from the class imbalance.

Input features in the data include:

<ul>
<li>Transaction amount</li>
<li>Merchant category for the transaction</li>
<li>Zip code for the merchant</li>
<li>Zip code for the billing address</li>
<li>Average transaction amount for the account over the past six months</li>
</ul>

Output feature:

<ul>
<li>0/1 flag for fraud (0 = not fraud, 1 = fraud)</li>
</ul>

Note: Fraudulent transactions are (thankfully) a very small percentage of all historical transactions. Assume fraudulent transactions are 0.01% of historical data.While building the model to perform the classification, you need to consider the bias/variance tradeoff, and take into account the fact that there is a class imbalance (very few of the observations are “fraud”).

You’re working as a biological data scientist at Columbia University on a research project that aims to automatically detect early-stage lung abnormalities from chest X-ray images. A senior researcher on the team suggests building a model based on handcrafted intensity-based markers, such as average pixel brightness in specific lung regions and simple texture statistics.

Another group proposes using a convolutional neural network (CNN) to learn features directly from the raw images, arguing it could capture more complex spatial patterns.

Both approaches have shown some promise in small pilot experiments, but you need to recommend a direction for the full study, where model interpretability, generalization across hospitals, and robustness to imaging differences are all important.

How would you evaluate these two modeling strategies? What factors would guide your investigation, and what evidence would you look for before deciding whether a CNN-based approach is justified over simpler intensity-based features?

Why do you want to use CNNs to classify X-ray images instead of using intensity-based markers?

CNNs vs Intensity-Based Features

What are the key differences between classification models and regression models?

What is the MOST important difference between regression and classification models?

What is the MOST important difference between regression and classification models?

Classification vs Regression

Let’s say you’re a data engineer at Fidelity Investments, and you’re running a SQL query on a cloud-based data warehouse. All cluster resources and network health metrics look normal, but the query is still taking over 10 minutes to complete.

How would you go about diagnosing and improving the performance of this query?

How would you diagnose and speed up a slow SQL query when system metrics look healthy?

Slow SQL Query

Query Optimization

Let’s say you’ve just finished building a churn prediction model for a subscription service, and the team is considering deploying it to automatically trigger retention emails for users at risk of leaving.

How would you ensure this model is ready for production, and what steps would you take to monitor its performance after launch?

How would you handle the data preparation for building a machine learning model using imbalanced data?

Addressing imbalanced data in machine learning through carefully prepared techniques.

Data Preparation for Imbalanced Data

How would you tackle multicollinearity in multiple linear regression?

You’re building a machine learning model to predict hospital readmission risk using patient records from the past five years. The data includes patient demographics, diagnoses, treatment history, and outcomes, but hospitals periodically change treatment protocols and data collection standards over time.

How would you structure your training, validation, and test splits to ensure your model generalizes to future patients? What risks would arise if these datasets were not clearly separated, and how would you validate that your final evaluation reflects real-world performance?

How would you structure your training, validation, and test splits to ensure your model generalizes to future patients? 

Training vs Validation vs Test Data

You are given a singly linked list, write a function to find and return the last node of the list. If the list is empty, return null.

Write a function to find and return the last node of a singly linked list. If the list is empty, return null.

Last Element of a Singly Linked List

Data Structures & Algorithms

Let’s say we’ve deployed a recommendation model for an e-commerce site, and after two months, we notice that the model’s click-through rate has dropped from 12% to 7%.

How would you investigate the cause of this performance decline, and what steps might you take to address it?

How would you investigate and address a decline in a model's production performance?

Model Product Performance Degradation

ML Ops

You work as a backend engineer at Glassdoor. The company relies on multiple legacy systems to aggregate and process job postings, salary data, and company reviews. To ensure reliable data ingestion and processing, you are tasked with building a monitoring service that tracks the health of these legacy systems via regular heartbeat signals.

The service must expose one endpoint to receive heartbeat signals from each legacy system, and another endpoint to return a list of systems that have not sent a heartbeat in the last five seconds. How would you architect this monitoring system? Write a technical design document describing your approach.

Design a monitoring service for legacy system health via heartbeat endpoints at Glassdoor.

Legacy System Heartbeat Monitor

DevOps

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

Your Strengths and Weaknesses

You work as a data engineer at Spotify. The executive team requests a weekly analytics report summarizing user engagement and streaming trends, using data from internal databases and log files. Strict budget constraints prohibit the use of commercial or managed cloud services; you must rely solely on open-source technologies such as PostgreSQL, Apache Airflow, Apache Spark, and Metabase.
How would you architect this reporting pipeline from data ingestion to report delivery?

Describe a time when you had to define a long-term vision for a project or team and move it from concept to reality.

Interviews for leadership or senior technical roles look for more than just “finishing a project.” Your answer should specifically address:

<ol>
<li>The “Why”: What data or organizational gap necessitated this vision?</li>
<li>The Framework: How did you translate a high-level goal into a roadmap?</li>
<li>The Friction: How did you handle stakeholders or team members who were skeptical of the new direction?</li>
</ol>

Talk about a time when you had trouble communicating with stakeholders. How were you able to overcome it?

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

Let’s say we’re launching a new version of the PayPal app, but due to a tight deadline, we don’t have time to run the entire suite of 300 automated test cases before release.

How would you handle this situation?

How would you approach limited testing time before a major app release?

Testing Constraints

A/B Testing

Let’s say you work as a data scientist on the engagement team.

<ol>
<li>How would you measure the success of Linkedin’s newsfeed ranking algorithm?</li>

<li>Let’s say some of the success metrics that you are tracking for the newsfeed algorithm are going up while others are going down. How would you approach this?</li>
</ol>

How would you convey insights and the methods you use to a non-technical audience?

Tell me about a project in which you had to clean and organize a large dataset.

Describing a real-world data cleaning and organization project

Data Cleaning Experiences

Analytics

Your company, a multinational retail corporation, has been storing sales data from various branches worldwide in separate tables according to the year the sales were made. The current data structure is proving inefficient for business analytics and the management has requested your expertise to streamline the data.

Write a query to create a pivot table that shows total sales for each branch by year.

Note: Assume that the sales are represented by the <code>total_sales</code> column and are in USD. Each branch is represented by its unique <code>branch_id</code>.

<h3>Example:</h3>

Input:

For simplicity, consider two years: 2021 and 2022.

<code>sales_2021</code> table

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

<tbody>
<tr>
<td>id</td>
<td>INTEGER</td>
</tr>

<tr>
<td>branch_id</td>
<td>INTEGER</td>
</tr>

<tr>
<td>total_sales</td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
<code>sales_2022</code> table

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

<tbody>
<tr>
<td>id</td>
<td>INTEGER</td>
</tr>

<tr>
<td>branch_id</td>
<td>INTEGER</td>
</tr>

<tr>
<td>total_sales</td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
Output:

<code>sales_pivot</code> table

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

<tbody>
<tr>
<td>branch_id</td>
<td>INTEGER</td>
</tr>

<tr>
<td>total_sales_2021</td>
<td>INTEGER</td>
</tr>

<tr>
<td>total_sales_2022</td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
This output pivot table shows the total sales for each branch, broken down by year.

Write a query to create a pivot table that shows total sales for each branch by year

Branch Sales Pivot

Challenge

<h3>Job Description</h3><div>Job Description<div>About the California Academy of SciencesFounded in 1853, the California Academy of Sciences is a globally renowned, AZA-accredited non-profit scientific and cultural institution located in the heart of San Francisco's Golden Gate Park. Home to a world-class planetarium, aquarium, rainforest, research institute, and natural history museum—all under one living roof—our mission is to regenerate the natural world through science, learning, and collaboration.Our living collection reflects Earth's vast biodiversity, consisting of nearly 60,000 animals representing over 800 species. Our research collections are the largest west of the Mississippi,  spanning nearly 46 million plants, animals, fossils, and cultural artifacts from across the globe and throughout history. Our diverse team includes leading biodiversity scientists, educators, storytellers, designers, and communicators who are passionate about advancing knowledge and catalyzing action through science and storytelling.Whether you're conducting research behind the scenes or engaging the public on the museum floor, your work will help connect people to the natural world and empower them to protect it.About the Opportunity The Product Manager for Web & Apps is the central owner of the Academy's public-facing website and select digital surfaces. The website is both a global science communication platform and one of the institution's most important revenue engines — driving ticket sales, membership enrollment and renewal, donations, event attendance, program registrations, retail purchases, and digital product engagement.This role blends product strategy, content platform leadership, UX rigor, experimentation, insight-driven decision-making, and complex cross-functional orchestration. You will shape how global audiences discover our science, plan their visit, support our mission, and return again and again, while managing a team of 4 to 6 direct reports who support the work.You will bring structure, clarity, and momentum to a large ecosystem of stakeholders — Science, Creative Studio, Marketing, Membership, Philanthropy, Education, Guest Experience, Sales, Operations, Business Applications, and Retail.What You Will Lead1. Ownership of the Website as a Revenue & Growth Engine You will drive measurable improvements across all revenue-critical flows, including:<ul><li>Ticketing and attendance growth</li><li>Membership join and renewal paths</li><li>Donor and philanthropic giving journeys</li><li>Event attendance and ticket sales</li><li>Educational program bookings</li><li>Retail and e-commerce (digital + physical)</li><li>Digital product engagement and monetization </li></ul>You will own the multi-year vision and roadmap to improve funnel efficiency, reduce friction between user and purchasing experience, and increase conversion across channels.2. Stewardship of the Digital Science & Storytelling Platform You will ensure the Academy's online presence:<ul><li>Makes scientific content accessible, engaging, and emotionally resonant</li><li>Translates research, exhibits, and conservation work into intuitive digital formats</li><li>Supports exhibitions, events, and programs through dynamic content</li><li>Maintains scientific accuracy, representational integrity, and public trust</li><li>Strengthens the Academy's voice in biodiversity, climate, and conservation</li></ul>3. Product Strategy & Multi-Year Roadmap You will:<ul><li>Define the long-term product vision across web and digital experiences</li><li>Maintain a sequenced roadmap for UX improvements, content evolution, revenue growth, and platform modernization</li><li>Align roadmap priorities with institutional goals and executive direction</li><li>Connect digital experiences to the Academy's Museum 3.0 transformation</li><li>Build structured processes for prioritization, resourcing, and trade-offs.</li></ul>4. Platform Modernization & Technical Excellence You will strengthen the Academy's digital foundation through:<ul><li>CMS improvements, structured content models, modular templates, and workflow upgrades</li><li>Performance, accessibility, and mobile-first optimization</li><li>SEO health, discoverability, and technical search improvements</li><li>Responsible use of AI tools for content creation, translation, optimization, and personalization</li><li>Close collaboration with Business Applications, Ops, and Sales to align digital flows with back-end ticketing, POS, CRM, and membership systems</li><li>Familiarity with Tessitura, Shopify, Stripe, Salesforce Commerce, WooCommerce, or similar tools (experience a plus, not required).</li></ul>5. Cross-Functional Alignment & Leadership You will unify and streamline collaboration across:<ul><li>Marketing & Communications: Audience growth, campaigns, acquisition, landing pages</li><li>Creative Studio: Design systems, visual identity, storytelling, component libraries</li><li>Science & Research: Accuracy, content translation, scientific integrity</li><li>Membership: Conversion, retention, segmentation, benefits communication</li><li>Philanthropy & Development: Donor journeys, fundraising pathways, impact storytelling</li><li>Guest Experience: Visit planning, wayfinding, operational clarity</li><li>Education & Events: School programs, family events, community learning</li><li>Retail & E-Commerce: Product sales, order flows, merchandise storytelling</li><li>Sales: Group sales, institutional offerings, partnerships</li><li>Operations & Business Applications: Ticketing, POS, identity systems, CRM, backend integrations</li></ul>You will define processes, establish decision-making frameworks, and ensure the website serves as a unified gateway to everything the Academy offers.Organizational CultureWhen you join the California Academy of Sciences, you become part of a mission-driven community that values curiosity, collaboration, and innovation, and celebrates its accomplishments together. Staff share a commitment to executing a new strategic plan that will strengthen the organization's financial foundations, cultivate a vibrant internal culture, and foster smart growth to secure the Academy's future.We hope you are inspired by what we do and are motivated to contribute to our mission. The Academy is looking for candidates who do great work, and we know they may come from a number of different backgrounds and experiences. We encourage you to apply even if you do not believe you meet every qualification for the position.This position is based in San Francisco, California. The specific onsite/hybrid schedule for this position is listed below.About the Experience & Revenue TeamThis role sits within the California Academy of Sciences' Experience & Revenue Division and reports directly to the Head of MarComm. The Experience & Revenue Division strengthens the Academy's relevance, reach, and revenue by uniting storytelling, design, science, and technology to reimagine how audiences engage with the Academy — onsite, online, and out in the world. We create emotionally resonant, insight-driven experiences that deepen belonging, spark wonder, and support financial sustainability through increased attendance, member engagement, donations, diversified revenue streams, and modern digital platforms. The Product Manager for Web & Apps is a central contributor to this mission.Key Responsibilities Revenue Growth & Conversion Optimization <ul><li>Own all digital funnels and conversion pathways</li><li>Build dashboards and analyses that reveal bottlenecks and drive enhancements</li><li>Lead A/B testing and experimentation cycles</li><li>Partner with Sales, Marketing, and Guest Experience to optimize acquisition and conversion</li><li>Drive continuous improvements in average order value and LTV</li></ul>Content & Experience Governance <ul><li>Establish content standards that ensure clarity, consistency, accuracy, and accessibility</li><li>Maintain information architecture, navigation, structured content, and taxonomy systems</li><li>Support sustainable content operations through improved workflows and governance</li><li>Balance scientific depth with an intuitive public-facing narrative</li></ul>UX, Design & Accessibility <ul><li>Lead UX improvements across critical user journeys</li><li>Maintain accessibility standards (WCAG 2.1+)</li><li>Partner with Creative Studio to sustain a cohesive, modern design system</li><li>Ensure mobile-first excellence across devices and browsers</li></ul>Execution, Delivery & Product Operations <ul><li>Own backlog prioritization and sprint planning</li><li>Write user stories, specs, and acceptance criteria</li><li>Manage QA, release readiness, and cross-team communication</li><li>Translate institutional goals into buildable, measurable digital initiatives</li></ul>Qualifications: A successful candidate will have the following: <ul><li>5 to 7+ years of product management experience with consumer-facing websites or digital content platforms</li><li>2+ years of experience leading a team.</li><li>Proven success optimizing revenue (ticketing, membership, donations, e-commerce)</li><li>Strong experience with CMS platforms, structured content, and workflow systems</li><li>Fluency in UX, analytics, SEO, IA, accessibility, and responsive design</li><li>Experience collaborating across creative, scientific, operational, and technical teams</li><li>Ability to lead through clarity, diplomacy, and structured decision-making</li><li>Analytical fluency with GA4 and experimentation frameworks</li><li>Exceptional communication skills — written, visual, and verbal</li></ul>Physical Environment: To perform this job successfully, an individual must be able to perform each essential job duty satisfactorily. Reasonable accommodations may be made to enable qualified individuals with disabilities to perform essential job functions. Compensation and Benefits: The salary range for this position is $110,000 - 120,000. Actual compensation will be commensurate with the final candidate's qualifications and experience, including skills, knowledge, relevant education, certifications and aligned with the internal peer group. We believe in fair and equitable compensation practices and are committed to providing competitive salaries within the industry and market standards. The Academy offers a total compensation package that emphasizes both base salary and comprehensive benefits based on the hours per week worked. Further details regarding compensation and benefits will be discussed during the interview process.Schedule: Full-time, 40 hours per week, hybridHow to Apply:  Interested candidates should submit a resume and application through our Careers Page portal.The California Academy of Sciences will give full consideration for employment to all qualified applicants with criminal histories in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance (SF Police Code, Article 49).</div></div>

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

California academy of sciences Interview Questions

California academy of sciences Interview Guides

California academy of sciences Interview Questions

Challenge

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