Overview
Build data science models and experimentation frameworks for WBD consumer platforms. Partner with engineering, product, and business teams to turn validated solutions into measurable product and business impact.
What you'll do
- Build models for identity resolution, audience modeling, personalization, forecasting, fraud detection, and lifecycle engagement.
- Design experiments, evaluation frameworks, baselines, success metrics, and promotion criteria.
- Partner with Machine Learning Engineers to operationalize models in scalable production pipelines.
- Frame ambiguous product and business opportunities as data science solutions.
- Communicate findings, tradeoffs, risks, and recommendations to technical and non-technical audiences.
- Define standards for feature and label quality, leakage prevention, evaluation, documentation, and production readiness.
What you'll need
- 3–5 years of experience building data science, statistical modeling, or machine learning solutions.
- Strong skills in translating business problems into hypotheses, problem statements, metrics, and recommendations.
- Practical knowledge of statistical modeling, machine learning, causal inference, experimentation, forecasting, ranking, recommendation, and model evaluation.
- Strong programming and analytical skills in Python and SQL.
- Experience with Databricks, Snowflake, AWS, MLflow, notebooks, experiment tracking, or similar tools.
- Experience partnering with Machine Learning Engineering or platform teams to operationalize models.
- Ability to explain technical methods, uncertainty, tradeoffs, and business implications clearly.
Nice to have
- Experience with Spark or large-scale distributed data processing.
- Master’s degree or Ph.D. in a quantitative field such as Computer Science, Statistics, Machine Learning, Data Science, Engineering, Mathematics, or Economics.
- Experience in streaming, media, advertising technology, identity, fraud, recommendations, personalization, forecasting, or audience intelligence.
- Experience with uplift modeling, causal impact analysis, lookalike modeling, clean-room analysis, graph-based methods, or multi-objective optimization.
Details
- Location: Hyderabad, India.
Read the full description and apply on the company’s own careers page.
