Description

Build data pipelines and apply causal inference methods to drive marketing insights and recommendations.

This role is on-site.

Responsibilities

• Build and optimize data pipelines with automation for data validation and unit testing.
• Refine and productionalize prototypes developed by the data science team.
• Develop and apply causal inference methods, specifically Marketing Mix Modeling (MMM), to estimate marketing effectiveness.
• Conduct data pulls, analyze trends, and engineer new features to support measurement efforts.
• Collaborate with cross-functional teams to provide insights that optimize marketing strategies.

Required Skills

• Ph.D. in Economics, Statistics, Marketing, or a related field, or Master’s Degree with 2+ years of experience.
• Proficiency in Python and R.
• Advanced SQL and database management skills.
• Experience with Apache Airflow and Apache Spark.
• Proven experience in Media Mix Modeling (MMM).
• Demonstrated ability to solve business problems using data science methods.
• Ability to communicate complex technical concepts to non-technical stakeholders.

Preferred Skills

• Familiarity with Bayesian modeling and causal ML modeling.
• Experience developing end-to-end models for data-driven decision-making.

Key Skills

Education

Bachelor's or Master's degrees