OpenAI
Leading AI research laboratory developing state-of-the-art foundation models like GPT-4.
5 Rounds
~21 Days
Very Hard
The Interview Loop
Recruiter Screen (30 min)
Standard fit check, behavioral questions, and resume overview.
Technical Loop (3-4 Rounds)
Deep dive into domain knowledge, coding, and system design.
Interview Question Bank
Data Scientist
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Behavioral
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medium
Tell me about a time you had to pivot your research or analysis because your initial hypothesis was completely invalidated by the data. How did you communicate this to stakeholders?
#Adaptability
#Communication
#Truth-seeking
Data Scientist
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Behavioral
•
medium
Describe a time you disagreed with an engineering lead or product manager about launching a model feature due to safety, bias, or data quality concerns. How did you resolve it?
#Conflict Resolution
#AI Safety
#Stakeholder Management
Data Scientist
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Behavioral
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medium
Tell me about a time you had to make a critical product or technical decision with highly ambiguous or incomplete data.
#Ambiguity
#Decision Making
#Risk Management
Data Scientist
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Behavioral
•
medium
OpenAI moves extremely fast. Tell me about a time you had to trade off rigorous statistical methodology for speed of execution.
#Speed vs Quality
#Pragmatism
#Execution
Data Scientist
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Behavioral
•
medium
Describe a situation where you strongly disagreed with a product manager or engineering lead about a metric or experiment result. How did you resolve it?
#Conflict Resolution
#Communication
#Stakeholder Management
Data Scientist
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Behavioral
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medium
Tell me about a time you discovered a critical flaw in your own analysis after it had already been shared with leadership or stakeholders.
#Integrity
#Accountability
#Continuous Improvement
Data Scientist
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Behavioral
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easy
How do you prioritize your work when you have multiple urgent, high-impact requests from different research and product teams?
#Prioritization
#Time Management
#Cross-functional
Data Scientist
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Behavioral
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medium
OpenAI's mission is to ensure AGI benefits all of humanity. How does this mission influence your day-to-day work and decision-making as a Data Scientist?
#Mission Alignment
#Ethics
#Safety
Data Scientist
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Behavioral
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medium
Tell me about a time you had to learn a completely new technical domain (e.g., a new ML architecture or infrastructure tool) in a very short amount of time to deliver a project.
#Adaptability
#Learning Agility
#Curiosity
Data Scientist
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Behavioral
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medium
Describe a project where you had to collaborate closely with engineering to get your data pipelines or ML models into production.
#Collaboration
#MLOps
#Productionization
Data Scientist
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Behavioral
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hard
What is the most complex data problem you have solved end-to-end, and what was the ultimate business impact of your solution?
#End-to-End Ownership
#Impact
#Technical Depth
Data Scientist
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Coding
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medium
Write a SQL query to calculate the week-over-week rolling retention rate for ChatGPT Plus subscribers, specifically isolating users who upgraded from the free tier within the last 30 days.
#Window Functions
#Cohorts
#User Retention
Data Scientist
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Coding
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hard
Given a stream of incoming API requests represented as tuples of (timestamp, user_id, token_count), write a Python algorithm to identify users who are consistently hitting the 99th percentile of token usage within any rolling 5-minute window.
#Streaming Data
#Sliding Window
#Heaps/Queues
Data Scientist
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Coding
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medium
Write a SQL query to find the top 1% of OpenAI API users by token volume who also have an error rate (e.g., HTTP 429 Rate Limit) exceeding 20% over the last 7 days.
#Percentiles
#Aggregations
#API Metrics
Data Scientist
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Coding
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medium
Given a list of user sessions containing timestamps and generated token counts, write an algorithm in Python to classify sessions as 'bot/scraper' vs. 'human' based on generation cadence and prompt frequency.
#Anomaly Detection
#Time Series
#Python
Data Scientist
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Coding
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medium
Write a SQL query to calculate the week-over-week retention rate of ChatGPT Plus users who utilized the Advanced Data Analysis feature within their first 3 days of upgrading.
#Retention
#Window Functions
#Cohorts
Data Scientist
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Coding
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medium
Using SQL, find the top 1% of API users by total token consumption over the last 30 days who also have a prompt-to-completion token ratio greater than 5:1.
#Percentiles
#Aggregations
#Filtering
Data Scientist
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Coding
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medium
Write a Python function to parse a massive JSONL file of ChatGPT conversation logs (too large to fit in memory) and compute the rolling 7-day average of messages per session.
#Data Generators
#Memory Management
#Time Series
Data Scientist
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Coding
•
hard
Implement a stratified sampling algorithm in Python to select prompt-response pairs for human evaluation (RLHF), ensuring proportional representation across 50 languages and 20 topic categories.
#Sampling
#Probability
#Data Structures
Data Scientist
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Coding
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hard
Design a SQL query to detect potential API key sharing by identifying accounts with requests originating from more than 5 distinct IP addresses within a rolling 10-minute window.
#Self-Joins
#Rolling Windows
#Anomaly Detection
Data Scientist
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System Design
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hard
Design a telemetry data pipeline to capture, process, and analyze user feedback (thumbs up/down and text corrections) on ChatGPT responses in real-time to trigger alerts for model degradation.
#Real-time Processing
#Streaming Architecture
#Data Pipelines
Data Scientist
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System Design
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hard
Design a system to monitor, detect, and alert on API latency degradation specifically for enterprise customers using provisioned throughput, ensuring a false positive rate of less than 1%.
#Monitoring
#Anomaly Detection
#Enterprise SLAs
Data Scientist
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System Design
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hard
Design the telemetry and analytics pipeline to track token usage, latency, and error rates for the OpenAI API in real-time.
#Streaming Architecture
#Telemetry
#Scalability
Data Scientist
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System Design
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hard
How would you design a system to detect and mitigate prompt injection attacks at scale before they hit the main inference cluster?
#Security
#Classification
#System Architecture
Data Scientist
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System Design
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medium
Design an analytics dashboard backend for OpenAI Enterprise customers to monitor their organization's usage, costs, and ROI.
#Data Modeling
#Multi-tenancy
#OLAP
Data Scientist
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System Design
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hard
Design a data pipeline to continuously update the knowledge cutoff of an LLM using web search data and news feeds.
#Data Pipelines
#Web Scraping
#Data Quality
Data Scientist
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Technical
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hard
How would you design an automated evaluation metric to detect and quantify hallucinations in a new iteration of the GPT-4 model without relying entirely on human annotators?
#LLM Evaluation
#Hallucination Detection
#Auto-Evals
Data Scientist
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Technical
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hard
We are A/B testing a new UI feature on ChatGPT that allows users to share interactive conversation snippets. How would you design the experiment to account for network effects and spillover?
#A/B Testing
#Network Effects
#Experiment Design
Data Scientist
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Technical
•
medium
ChatGPT Daily Active Users (DAU) dropped by 5% week-over-week, but API usage increased by 10%. Walk me through your diagnostic process to find the root cause.
#Root Cause Analysis
#Metric Trees
#Cannibalization
Data Scientist
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Technical
•
hard
Explain the statistical and practical trade-offs between using Reinforcement Learning from Human Feedback (RLHF) versus Direct Preference Optimization (DPO) for aligning a language model.
#RLHF
#DPO
#Model Alignment
Data Scientist
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Technical
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hard
How do you determine the required sample size for a prompt-variation A/B test when the primary evaluation metric is subjective human preference (e.g., Elo rating)?
#Power Analysis
#Elo Ratings
#Variance Estimation
Data Scientist
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Technical
•
medium
How would you identify and mitigate bias in a dataset used to fine-tune our moderation endpoint to ensure it doesn't disproportionately flag text from specific demographic dialects?
#Bias Mitigation
#Data Quality
#Content Moderation
Data Scientist
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Technical
•
hard
We are considering introducing a new pricing tier for the API based on compute time rather than purely on token count. How would you model the financial impact and predict user churn?
#Pricing Models
#Forecasting
#Churn Prediction
Data Scientist
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Technical
•
hard
How would you design an A/B test to evaluate a new model routing algorithm (e.g., dynamically routing between GPT-4o and GPT-4-turbo) where the primary metric is perceived user latency?
#Experiment Design
#Latency Metrics
#Trade-offs
Data Scientist
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Technical
•
hard
ChatGPT responses are highly non-deterministic. How do you measure the statistical significance of a system prompt change on overall response quality?
#Variance Reduction
#LLM Evaluation
#Hypothesis Testing
Data Scientist
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Technical
•
hard
Explain how you would handle network effects in an A/B test for a new collaborative workspace feature in ChatGPT Enterprise.
#Network Effects
#Cluster Randomization
#Enterprise Analytics
Data Scientist
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Technical
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medium
We want to introduce a new dynamic usage cap for GPT-4 based on server load. How would you determine the optimal threshold to minimize user churn while maximizing compute savings?
#Optimization
#Churn Prediction
#Capacity Planning
Data Scientist
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Technical
•
medium
What metrics would you define to evaluate the success and adoption of the 'Custom Instructions' feature in ChatGPT?
#Metric Definition
#Product Sense
#User Engagement
Data Scientist
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Technical
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medium
You run an A/B test on a new moderation endpoint. The false positive rate drops by 2%, but latency increases by 50ms. How do you decide whether to ship it?
#Trade-offs
#Decision Making
#Safety
Data Scientist
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Technical
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hard
How would you estimate the cannibalization effect of releasing a cheaper, faster model (like GPT-4o mini) on our flagship model's API revenue?
#Causal Inference
#Cannibalization
#Forecasting
Data Scientist
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Technical
•
hard
How do you evaluate the quality of text embeddings generated by our API without relying entirely on downstream task performance?
#Embeddings
#Unsupervised Evaluation
#NLP
Data Scientist
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Technical
•
hard
Explain the trade-offs between using RLHF (Reinforcement Learning from Human Feedback) versus DPO (Direct Preference Optimization) from a data collection and evaluation standpoint.
#RLHF
#DPO
#Model Alignment
Data Scientist
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Technical
•
hard
How would you build an automated metric to quantify 'hallucinations' in a RAG-based enterprise deployment?
#Hallucination Detection
#RAG
#LLM-as-a-judge
Data Scientist
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Technical
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hard
We notice a degradation in coding performance (e.g., HumanEval scores) in the latest model checkpoint. How do you investigate if this is a real regression or an artifact of the evaluation set?
#Model Evaluation
#Debugging
#Data Contamination
Data Scientist
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Technical
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hard
Describe how you would design a reward model for a specific domain, like medical advice, where accuracy is critical but human raters might frequently disagree.
#Reward Models
#Data Annotation
#Domain Expertise
Data Scientist
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Technical
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medium
What is perplexity, and why is it sometimes a misleading metric for evaluating the final conversational quality of an aligned LLM?
#Perplexity
#Information Theory
#Model Alignment
Data Scientist
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Technical
•
medium
How would you cluster millions of user prompts to identify emerging use cases for ChatGPT without manually labeling the data?
#Clustering
#Topic Modeling
#Unsupervised Learning
Data Scientist
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Technical
•
hard
If we want to personalize the ChatGPT experience based on past interactions, what data points would you use and how would you evaluate the risk of catastrophic forgetting in the model?
#Personalization
#Continual Learning
#Memory
Data Scientist
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Technical
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hard
Walk me through how you would price a new multimodal API endpoint (e.g., video generation). What data do you need to make this decision?
#Pricing Strategy
#Unit Economics
#Market Analysis
Data Scientist
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Technical
•
medium
ChatGPT Daily Active Users (DAU) is dropping in a specific region. Walk me through your diagnostic process to identify the root cause.
#Root Cause Analysis
#Product Metrics
#Debugging
Difficulty Radar
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Meet Your Interviewers
The "Standard" Interviewer
Senior EngineerFocuses on core competencies, system constraints, and clear communication.
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Think Out Loud
Always explain your thought process before writing code or drawing architecture.