Senior Data Scientist developing advanced measurement models to support decision-making across teams. Focusing on causal inference and performance evaluation in technology-oriented industries.
Responsibilities
Build and apply attribution and causal models (e.g., multi-touch attribution, experimental design).
Design and analyze experiments to evaluate program effectiveness and user behavior.
Apply best practices in causal inference and statistical modeling.
Translate business objectives into measurable outcomes.
Deliver insights on performance, lifetime value, and incremental impact.
Collaborate with cross-functional teams to implement measurement frameworks.
Requirements
Bachelor's degree in Statistics, Econometrics, Economics, Data Science, or a related field.
5–10 years of experience in measurement, attribution, or applied data science.
Proficiency in R (preferred) or Python for statistical modeling and experimentation.
Experience with modern data platforms such as Databricks and Redshift in production environments.
Expertise in A/B testing, causal inference, and advanced modeling techniques.
Ability to work across technical and non-technical teams in a matrixed environment.
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