About The Role

Experience with cloud computing platforms (e.g., AWS, Google Cloud)
Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch)
Knowledge of data visualization tools (e.g., Tableau, Power BI)
Experience with version control systems (e.g., Git)
Understanding of data privacy regulations and best practices
Design, validate, and deploy robust, scalable optimization frameworks and distribution models to ensure complete mathematical integrity across downstream metrics.
Explore and execute complex methodologies, evaluate methodological trade-offs, and implement advanced statistical procedures.
Partner cross-functionally to transition ad hoc code into standardized, version-controlled templates and logical libraries, ensuring analytics are structured cleanly.
Experience: 4–5 years of professional data science experience. 2-3 years of experience with an advanced degree
Direct experience working with panel data or longitudinal consumer data
Experience working with Databricks and scaling advanced compute workloads
Mathematical Proficiency: Exceptional expertise in working with, modeling, and optimizing for statistical distributions
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
Hands-on experience analyzing receipt data or transaction-level consumer data
Technical Stack: Advanced proficiency in Python or R and expert-level SQL
Key Advantages (Big Plus):

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Data Scientist (Corporate)

About The Role