Participate in the full modeling lifecycle, from statistical analysis and experimentation to building, validating, and iterating on machine learning models that address critical business challenges
Own the data foundation by preparing, cleaning and transforming raw, complex data into high-quality features for modeling
Investigate data discrepancies and design automated frameworks to ensure data accuracy
Act as a strategic liaison, collaborating with data engineering and product teams to drive the data strategy and definition of our centralized feature store
Create and maintain clear documentation for data sources, cleaning processes, and variable definitions

Requirements

Bachelor’s degree (PhD preferred) in a quantitative field (Statistics, Physics, Mathematics, etc.)
Strong proficiency in Python (Pandas/NumPy) and SQL for complex querying and data manipulation
Hands-on experience with data cleaning techniques and data validation frameworks
Familiarity with data visualization tools to help identify and communicate data issues

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningstatistical analysisdata cleaningdata validationPythonPandasNumPySQLdata visualization

Soft Skills

collaborationcommunicationdocumentation

Certifications

Bachelor's degreePhD