Senior Data Scientist
Build and ship forecasting, promotion-effectiveness, and data-quality models using complex retail and CPG data. The role requires 5+ years of data science experience, strong statistical foundations, and fluency in Python and SQL.
About the job
Responsibilities
- Build demand and sales forecasting models across noisy retail time series.
- Measure promotion lift, price elasticity, and cannibalization to inform promotional strategy.
- Develop data-quality checks and evaluation methods for incoming data and model outputs.
- Turn exploratory analyses into production-grade insights shipped inside the product.
- Collaborate with AI/ML engineers and communicate findings to both technical and non-technical stakeholders.
- Validate analyses, perform sanity checks, and communicate uncertainty.
Requirements
- 5+ years of hands-on data science experience with real-world data.
- Strong statistical foundations in regression, time-series methods, experiment design, and uncertainty quantification.
- Fluency in Python and SQL.
- Experience with modern data stacks, including Snowflake and dbt.
- Ability to explain models to non-technical operators and defend methodology to ML engineers.
Nice-to-haves
- Experience with retail, CPG, supply chain, or demand-planning data.
- Experience shipping models into production systems.
- Familiarity with forecasting at scale, including hierarchical forecasting and intermittent demand.
Compensation and Benefits
- $250,000–$300,000 annual salary.
- Equity.
- Fully paid employee health coverage, dental and vision coverage.
- Fertility and family-forming support.
- 12 weeks of paid parental leave.
- Unlimited PTO and regular four-day holiday weekends.
- 401(k).
- Paid relocation support.
- Workspace equipment and a $200 setup stipend.
Skills
Python, SQL, Snowflake, dbt, AWS, Regression, Time-Series Analysis, Experiment Design, Uncertainty Quantification, Hierarchical Forecasting, Intermittent Demand
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