Data Scientist
Build and ship forecasting, promotion-effectiveness, and data-quality models using retail and CPG data. The role requires 3–5 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 statistical evaluation methods for model reliability.
- Turn exploratory analyses into production-grade insights shipped inside the product.
- Collaborate with AI/ML engineers and communicate findings to technical and non-technical stakeholders.
Requirements
- 3–5 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 validate analyses, sanity-check results, communicate uncertainty, and explain models clearly.
Nice-to-haves
- Experience with retail, CPG, supply-chain, or demand-planning data.
- Experience shipping models into production systems.
- Familiarity with forecasting at scale, hierarchical forecasting, or intermittent demand.
Compensation and Benefits
- Equity.
- Fully paid employee health coverage through Aetna.
- Dental and vision coverage through Guardian.
- Fertility and family-forming support through Carrot Fertility Pro.
- 12 weeks of paid parental leave.
- Unlimited PTO and regular four-day holiday weekends.
- 401(k) through Vestwell.
- Paid relocation support to NYC.
- Equipped workspace, including laptop, monitor, keyboard, and a $200 setup stipend.
- Catered lunches, team dinners, coffee, and snacks.
Skills
Python, SQL, Snowflake, dbt, AWS, Regression, Time-Series Analysis, Experiment Design, Uncertainty Quantification, Demand Forecasting, Hierarchical Forecasting, Intermittent Demand
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