Senior Data Scientist

Responsibilities

• Build statistical and machine learning models to improve content discovery and user engagement.
• Work closely with ML engineers to translate models and insights into production systems.
• Have curiosity and apply analytical skills to dive deep into data to find key insights that would impact the business.
• Apply causal inference methods to understand the impact of potential product changes.
• Define and build new ML features using text and multimodal embeddings and GenAI.
• Validate offline learnings with online outcomes through AB testing. Design, execute, and analyze experiments to prove product change attribution.

Preferred

• Experience working on consumer-facing products with millions of users.
• Hands-on experience with orchestration/transformation tools (e.g. dbt and Airflow).
• Experience with deep learning and being familiar with tools such as PyTorch or TensorFlow.
• Hands-on development of products/tools incorporating GenAI, LLMs, RAG, and/or Agents.

MINIMUM QUALIFICATIONS

PhD or M.S. in Computer Science, Mathematics, Electrical Engineering, Statistics, Economics or Operations Research with 5+ years of professional experience in data science, machine learning or related quantitative field

3+ years of professional experience with large-scale online ranking/recommender systems (for news feeds, shopping, ads, music, etc).

Deep expertise in statistical inference and experimental design: hypothesis testing, power/sample size calculations, variance reduction, etc.

Proficiency in causal inference methods to measure product impact.

Proven ability to translate offline analysis into product decisions and measurable improvements in online metrics.

Fluency in the Python analytics stack (pandas, NumPy), statistical modeling (statsmodels or scikit-learn) and machine learning packages such as LightGBM and XGBoost.

Strong experience with SQL (e.g. postgres, snowflake, etc).