Senior Data Scientist (Causal Inference, Econometrics, Experimental Design)

A fast-growing analytics startup and they are seeking a Senior Data Scientist to join its fully remote team. This is a full-time, 100% US remote opportunity focused on building advanced causal inference and measurement solutions that help lead consumer brands optimize business decisions. You'll work at the intersection of machine learning, economics, and experimental design in a highly research-driven environment.

This is a unique opportunity to help bridge cutting-edge academic research and real-world business impact. You'll collaborate directly with an experienced data science team and advisors from top research institutions while helping develop production-grade causal inference models used by enterprise customers. The company offers the autonomy, ownership, and growth potential of an early-stage startup backed by experienced founders with successful exits.

Required Skills & Experience

• Master's degree required; PhD strongly preferred in Statistics, Economics, Computer Science, Mathematics, or a related quantitative field
• Deep expertise in Causal Inference
• Experience with Difference-in-Differences (DiD)
• Strong understanding of Causal Graphs / Directed Acyclic Graphs (DAGs)
• Python and modern data science tooling

Desired Skills & Experience

• PhD in quantitative discipline
• Published research involving causal inference or econometrics
• Experience deploying analytical models into production
• Experience with retail, CPG, marketing measurement, or consumer analytics
• Machine learning and experimentation background

What You Will Be Doing Tech Breakdown

• 70% Causal Inference & Econometric Modeling
• 20% Experimental Design & Statistical Analysis
• 10% Machine Learning & Data Science Tools

Daily Responsibilities

• 80% Hands-On Modeling & Research
• 10% Cross-Functional Collaboration
• 10% Customer & Business Impact Initiatives

The Offer You Will Receive The Following Benefits

• Competitive base salary
• Equity opportunity
• Fully remote work environment
• High-growth startup opportunity
• Direct exposure to executive leadership and academic advisors
• Long-term leadership growth potential

Applicants must be currently authorized to work in the US on a full-time basis now and in the future.

Posted By: Tariq Othman