Sr Data Scientist, Demand Planning

Turbo Tax Live Full Service is one of Intuit’s fastest‑growing and most operationally complex offerings, connecting customers with expert tax preparers to complete their returns end‑to‑end. Demand planning is mission‑critical: too little supply means customers wait; too much means stranded expert capacity and margin pressure.

• Own end‑to‑end demand forecasting for Full Service, from early‑season outlook through real‑time in‑season adjustments.
• Build and maintain models that translate customer funnel signals (trade‑up rates, FSO attach, offer acceptance) into demand inputs for capacity planning.
• Develop interval‑level, daily, and weekly forecasts that feed directly into staffing and partner capacity decisions across internal, JDA, CNX, and other TPA channels.

• Advance forecasting methodology—incorporating time‑series models, regression‑based approaches, and ML techniques to improve accuracy and reduce forecast error.
• Build scenario models and confidence intervals to support risk quantification (e.g., upside/downside demand cases for peak season planning).
• Explore and incorporate new signal sources: marketing spend curves, product funnel data, historical tax filing trends, macroeconomic indicators.

• Serve as the embedded DS partner for Workforce Management and Capacity Planning, translating model outputs into staffing recommendations and operational levers.
• Partner with Finance on demand‑to‑revenue reconciliation and capacity cost modeling.
• Collaborate with Marketing and Product on offer strategy and its downstream demand impact (e.g., FSO trade‑up promotions, LT offer windows).

• Support real‑time in‑season analytics—tracking WIP burndown, FSO funnel conversion, and coverage gap signals.
• Build and maintain dashboards and data products that surface demand risk to operational and leadership audiences.
• Contribute to post‑season retrospectives on forecast accuracy, bias analysis, and methodology improvements.

• Write and maintain production‑quality SQL and Python code against Intuit’s data lake (e.g., capacityplandatasetv3, FSO funnel tables, expert supply tables).
• Partner with Data Engineering to improve upstream data quality and pipeline reliability for forecasting use cases.
• Document models, assumptions, and methodologies to enable reproducibility and stakeholder trust.

• 3+ years of experience in data science or quantitative analytics, with a focus on forecasting, demand planning, or supply‑demand modeling.
• Strong proficiency in Python (pandas, stats models, scikit‑learn) and SQL across large‑scale data environments.
• Hands‑on experience building and deploying time‑series or demand forecasting models in a production or operational context.
• Demonstrated ability to work cross‑functionally and communicate model outputs to non‑technical stakeholders, including senior leaders.
• Comfort operating in ambiguous, fast‑moving environments—particularly during high‑stakes operational windows.
• Bachelor’s or Master’s degree in Statistics, Data Science, Operations Research, Mathematics, or a related quantitative field.

San Diego $149,500 - $202,500