Senior Data Scientist / Lead Data Scientist - Causal Modeling

About the Role

Data Scientist /Sr Data Scientist / Lead Data Scientist with expertise in Causal Modeling

Key Responsibilities

• Design and implement

  causal inference frameworks

  to measure the true impact of business initiatives, marketing campaigns, and product interventions.
• Apply methods such as

  propensity score matching, instrumental variables, difference-in-differences, regression discontinuity, uplift modeling, and causal graphs

  .
• Build and validate robust statistical and machine learning models to support experimentation (A/B testing, quasi-experiments).
  
• Partner with cross-functional teams (product, marketing, operations, data engineering) to define problems, frame hypotheses, and deliver actionable insights.
  
• Develop scalable analytical pipelines and dashboards for causal impact monitoring.
  
• Stay up to date with advances in

  econometrics, Bayesian methods, and causal ML techniques

  .

Required Skills & Qualifications

• Masters or PhD in

  Statistics, Econometrics, Computer Science, Mathematics, Economics, or a related field

  .
• 3–10 years of experience as a

  Data Scientist / Quantitative Researcher / Econometrician

  .
• Strong knowledge of

  causal inference methods and experimental design

  .
• Proficiency in

  Python / R / SQL

  for data manipulation, statistical modeling, and visualization.
• Experience with

  ML frameworks

  (scikit-learn, PyTorch, TensorFlow) is a plus.
• Strong analytical mindset with the ability to translate complex results into clear business recommendations.
  

Good to Have

• Experience in

  forecasting, recommendation systems, or optimization

  .
• Exposure to

  big data tools

  (Spark, Snowflake, Databricks, etc.).
• Publications or applied research in causal inference or related fields.