Sr. Research Data Scientist

Responsibilities

• Design and build a causal inference platform for measuring customer actions' impact
• Research and implement causal estimation methods tailored to the company’s data
• Build frameworks for long-term outcome projections from limited observation data
• Develop diagnostic standards to ensure the credibility of causal estimates
• Use AI to create counterfactual scenarios and enhance decision-making tools
• Collaborate with cross-functional teams to translate business questions into causal analyses
• Contribute to the technical vision of the Data Science team in causal inference and data experimentation

Qualifications

• PhD in Economics, Econometrics, Statistics, or related field with a focus on causal inference
• 10+ years of experience in causal inference and machine learning applied to real-world problems
• Expertise in observational causal methods including propensity score matching and difference-in-differences
• Experience in building reusable causal inference tools or platforms
• Proficient with Spark, Ray, SQL, Python, and ML frameworks like scikit-learn and XGBoost
• Familiar with handling terabyte or petabyte-scale datasets in distributed environments
• Strong communication skills for translating econometric findings into business strategies

Benefits

• Global access to mental health and financial wellness support
• Healthcare benefits including medical, dental, and vision
• Life and disability insurance options
• Commute benefits and retirement options (401(k)/pension)

Pay

$330,000 – $375,000 annually

Schedule

Not specified

Benefits

• Commute benefits and retirement options (401(k)/pension)

Skills

• Econometrics
• Statistics
• Machine Learning
• Observational Causal Methods
• Propensity Score Matching
• Difference-in-Differences
• Spark
• Ray
• SQL
• Python
• ML Frameworks (scikit-learn, XGBoost)

Location

New York, NY - US based candidates only, no visa sponsorship available

Company Information

Our client is an equal opportunity employer.