Data Scientist, Corporate

About the role

We are looking for a Data Scientist to join our core Panel Science team. Our team is dedicated to building an uncompromising, mathematically rigorous single source of truth for enterprise consumer analytics. In this role, you will work across a highly sophisticated data engine that bridges foundational statistical modeling, complex data infrastructure, and advanced analytical product architecture.

Responsibilities

• Statistical Modeling & Distribution Optimization: Design, validate, and deploy robust, scalable optimization frameworks and distribution models to ensure complete mathematical integrity across downstream metrics.
• Methodology & Panel Foundations: Explore and execute complex methodologies, evaluate methodological trade-offs, and implement advanced statistical procedures.
• Analytical Logic & Governance: Partner cross-functionally to transition ad hoc code into standardized, version-controlled templates and logical libraries. Ensure analytics are structured cleanly to power diverse product surfaces, ranging from interactive dashboards to LLM-driven applications.
• Infrastructure & Performance Optimization: Partner closely with Data Engineering to optimize code performance and scale analytical workflows. Help transition complex statistical calculations from standard database queries into efficient, production-grade cloud compute architectures.

Requirements

• Experience: 4–5 years of professional data science experience. 2-3 years of experience with an advanced degree.
• Education: Bachelor’s degree in a highly quantitative field (Statistics, Economics, Physics, Mathematics, Engineering, or a related discipline). A Master’s degree is strongly preferred.
• Mathematical Proficiency: Exceptional expertise in working with, modeling, and optimizing for statistical distributions.
• Technical Stack: Advanced proficiency in Python or R and expert-level SQL.

Qualifications

• Direct experience working with panel data or longitudinal consumer data.
• Hands-on experience analyzing receipt data or transaction-level consumer data.
• Experience working with Databricks and scaling advanced compute workloads.