Data Scientist

Key Responsibilities

• Develop and enhance Marketing Mix Models (MMM) to measure channel effectiveness, optimize budget allocation, and quantify marketing ROI.
• Rewrite and refine Customer Lifetime Value (CLV) models to improve acquisition, retention, and customer segmentation strategies.
• Design, execute, and analyze A/B tests and quasi-experimental studies, including: Difference-in-Differences, Synthetic Controls, Geo Holdouts, Propensity Scoring, Instrumental Variables.
• Evaluate the incremental impact of marketing initiatives through rigorous causal inference methodologies.
• Translate analytical findings into actionable recommendations for campaign targeting, creative strategy, and channel optimization.
• Partner with data scientists, machine learning engineers, and business stakeholders to deploy measurement solutions into production environments.
• Conduct exploratory research and develop innovative methodologies to better understand customer behavior and marketing effectiveness.
• Communicate complex technical concepts and research findings to both technical and non-technical audiences.

Required Qualifications

• PhD, or Master’s degree with 4+ years of experience in: Statistics, Economics, Computer Science, Machine Learning, Operations Research, or a related field.
• Strong experience with causal inference methodologies including: A/B Testing, Difference-in-Differences, Propensity Score Methods, Instrumental Variables, Synthetic Controls.
• Experience with cloud computing platforms and distributed analytics environments.
• Strong programming skills in Python, R, or similar analytical languages.
• 3+ years of experience building machine learning models or developing analytical solutions for business applications.

Top Required Skills

• Causal Inference: Deep understanding of experimental and quasi-experimental methodologies used to measure incremental business impact.
• Experiment Design: Experience designing, executing, and evaluating A/B tests and large-scale marketing experiments.
• Cloud Computing: Experience leveraging cloud-based tools and platforms to support large-scale data science and modeling initiatives.

Preferred Qualifications

• PhD in Statistics, Economics, Computer Science, Machine Learning, Operations Research, or a related field.
• 5+ years of experience building: Marketing Mix Models (MMM), Customer Lifetime Value (CLV) models, Multi-Touch Attribution frameworks.
• Experience designing and analyzing large-scale geo experiments.
• Publishations or patents demonstrating advanced research expertise.
• Strong communication skills with the ability to present complex findings to leadership and business stakeholders.

Ideal Candidate Profile

• Successful Candidates Typically Come From Marketing Science, Data Science, Applied Economics, Machine Learning, Quantitative Research, Advanced Analytics.
• Track Record of Using Statistical Methods and Experimentation to Solve Complex Business Problems and Drive Measurable Outcomes.
• Comfortable Conducting Advanced Statistical Research and Translating Insights into Business Action.
• Strong Expertise in Marketing Measurement, Experimentation, and Causal Inference.
• Able to Develop Scalable Analytical Solutions That Influence Strategic Decision-Making Across the Organization.