Headspace
Digital Health
PrincipalDataScientist
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“Principal Data Scientist at Headspace. Skills: forecasting, experimentation, statistical modeling, causal inference, data products, SQL, Python. Own and evolve end-to-end demand and supply forecasting. Develop high-accuracy forecasting models”
What You'll Achieve.
lead the evolution of data science across our care delivery and marketplace ecosystem; enabling us to deliver high-quality, accessible mental healthcare at scale; uncovering insights that power Headspace’s mission to provide lifelong mental health support; shaping how Headspace forecasts demand and supply, optimizes marketplace performance, and measures clinical and coaching outcomes; design and deploy advanced analytical solutions that directly influence business strategy and member experience; improve capacity planning and resource allocation; ensure reliable predictions and scalable recommendations; optimize access, capacity, and fulfillment performance; ensure they are reliably captured and reported; ensure high data quality and instrumentation completeness; translate outcome insights into product, clinical, and operational improvements; enable self-service insights and automation; raising the bar for analytical rigor across the organization; driving alignment and action
Industry & Context.
strategic; impact-driven; uncovering insights; analytical rigor
Candidates must permanently reside in the US full-time., For candidates with a primary residence in the greater SF area, this role will follow our hybrid model. You’ll work 3 days per week from our office, allowing for impactful in-office collaboration and connection, while enjoying the flexibility of remote work for the rest of the week.
What They're Looking For.
Must Have
8+ years of well-rounded analytics and data science experience, 6+ years of experience successfully partnering directly with executive leadership and product leaders, Proven experience building and deploying forecasting models, optimization solutions and decision frameworks in complex, real-world environments, expertise in statistical modeling, causal inference, and experimentation, 6+ years of experience owning and managing data products while driving their strategic utilization to create business impact, Advanced skills in SQL and Python, Bachelor's or master's degree in computer science, statistics, mathematics, or a related quantitative field
Nice to Have
exposure to Digital Health, high-growth SaaS, and/or Mental Health industries in rapid growth environments, 4+ years of progressive experience in healthcare analytics, Looker, Tableau, Amplitude, Statsig for event-based deep dives and advanced analytics also preferred
What You'll Do.
Own and evolve end-to-end demand and supply forecasting
Develop high-accuracy forecasting models
Identify and translate drivers of demand variability into actionable operational levers
Build forecasting and shift optimization systems
Enable marketplace leaders with data-driven insights
Define and standardize clinical and coaching outcome metrics
Lead the development of end-to-end measurement frameworks for care journeys
Apply causal inference and statistical modeling to evaluate engagement
and long-term member outcomes
Build and scale data products
forecasting pipelines
and decision-support tools
Collaborate with Data Engineering and BI to define robust data models
Translate complex models into intuitive dashboards and tools
Drive new uses of AI in analytics and forecasting
Mentor and develop data scientists and analysts
How You'll Work.
Team & Collaboration
Working closely with leaders across Product, Care, Operations, Finance, Engineering, and Marketing; Partner with cross-functional leaders; Collaborate with Data Engineering and BI; Communicate complex findings clearly to executive and non-technical audiences; partner on the ROI dashboards; Mentor and develop data scientists and analysts, strengthening capabilities in communication, stakeholder influence, and technical execution
Communication Scope
Communicate complex findings clearly to executive and non-technical audiences; driving alignment and action; strengthening capabilities in communication
Process & Methodology
Own and evolve end-to-end demand and supply forecasting, Lead the development of end-to-end measurement frameworks, Build and scale data products, forecasting pipelines, and decision-support tools
Full Job Description
About the Principal Data Scientist at Headspace: We are looking for an innovative, strategic and impact- driven Principal Data Scientist to lead the evolution of data science across our care delivery and marketplace ecosystem. This role sits at the intersection of forecasting, experimentation, and workforce optimization strategy, enabling us to deliver high-quality, accessible mental healthcare at scale. You will be designing analytical frameworks, developing data science products, and uncovering insights that power Headspace’s mission to provide lifelong mental health support. You will play a critical role in shaping how Headspace forecasts demand and supply, optimizes marketplace performance, and measures clinical and coaching outcomes. Working closely with leaders across Product, Care, Operations, Finance, Engineering, and Marketing, you will design and deploy advanced analytical solutions that directly influence business strategy and member experience. This is a high-impact leadership role for a seasoned data scientist who combines deep technical expertise, strong business intuition, and a passion for improving mental health outcomes. What you will do: Own and evolve end-to-end demand and supply forecasting at both macro and shift levels for care services (coaching, therapy, psychiatry), incorporating behavioral, operational, and external drivers. Develop high-accuracy forecasting models to support new product launches and partnerships (e.g., large-scale enterprise or channel launches). Identify and translate drivers of demand variability into actionable operational levers that improve capacity planning and resource allocation. Build forecasting and shift optimization systems that integrate multi-modal data sources (including B2B/enterprise signals) to ensure reliable predictions and scalable recommendations. Enable marketplace leaders with data-driven insights to optimize access, capacity, and fulfillment performance. Partner with cross-functional leaders to de
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