Sr Data Scientist, Demand Planning

Intuit offers a benefits-forward culture with a cash bonus, equity rewards, and a comprehensive benefits package. This on-site role is based in San Diego, CA.

Location: San Diego, CA (onsite)

Salary: USD 149,500 - 202,500 per year

Overview

Intuit is seeking a Senior Data Scientist to own demand planning for the Full Service offering within the Consumer Group's Expert Network. You will be the primary modeler and analyst for forecasting Full Service Order volume, translating funnel signals into staffing inputs, and improving forecast accuracy across pre-season, in-season, and off-season horizons. This is an individual-contributor role with high visibility and cross-functional influence on workforce decisions.

What you will do

• Lead end-to-end demand forecasting for Full Service, from early-season outlook to real-time in-season adjustments
• Develop and maintain models that convert funnel signals (trade-up rates, FSO attach, offer acceptance) into actionable demand inputs for capacity planning
• Produce interval-level, daily, and weekly forecasts that inform staffing and partner capacity across internal systems and external channels
• Advance forecasting methodology by blending time-series models, regression approaches, and machine learning techniques to improve accuracy
• Build scenario models with confidence intervals to quantify risk, including upside and downside demand cases for peak season
• Explore and incorporate new signal sources such as marketing spend curves, product funnel data, historical tax filing trends, and macro indicators
• Serve as the embedded data science partner for Workforce Management and Capacity Planning, translating outputs into staffing recommendations and operational levers
• Collaborate with Finance on demand-to-revenue reconciliation and capacity cost modeling
• Work with Marketing and Product on offer strategy and its downstream demand impact, including FSO trade-up promotions and 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 datalake datasets related to capacity planning and FSO funnels
• 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

Requirements

• 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, statsmodels, scikit-learn) and SQL in large-scale data environments
• Hands-on experience building and deploying time-series or demand forecasting models in production or operational contexts
• Ability to work cross-functionally and communicate model outputs to non-technical stakeholders, including senior leaders
• Comfort operating in ambiguous, fast-moving environments, especially during high-stakes operational windows
• Bachelor's or Master's degree in Statistics, Data Science, Operations Research, Mathematics, or related quantitative field

Technologies

• Python
• SQL
• pandas
• statsmodels
• scikit-learn
• datalake

Benefits

• Cash bonus
• Equity rewards
• Benefits