Data Scientist, Corporate

Our data and research teams transform raw data into strategic intelligence, delivering accurate, timely, and deeply contextualized analysis that our customers—ranging from the world’s top investment funds to Fortune 500 companies—depend on to drive high-stakes decisions. From sourcing and licensing novel datasets to...

We operate globally with offices in the US, APAC, and India. Our award-winning, people-centric culture—recognized by Inc. as a Best Workplace for three consecutive years—emphasizes transparency, ownership, and continuous mastery.

YipitData isn’t a place for coasting—it’s a launchpad for ambitious, impact-driven professionals.

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. Whether your deep expertise lies in refining core statistical baselines, optimizing heavy computational models, or architecting scalable logic libraries, you will have a massive impact on how enterprise-level consumer insights are delivered.
This is a remote-friendly opportunity that can sit in NYC (where our headquarters is located), one of our office hubs, or anywhere else in the US. However, depending upon where the remote work is performed, income could be subject to New York State tax withholding. We expect East Coast work hours.
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. You will 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. You will help transition complex statistical calculations from standard database queries into efficient, production-grade cloud compute architectures.
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.
Key Advantages (Big Plus):
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.