About the Role
Headspace is seeking 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 focuses on forecasting, experimentation, and workforce optimization strategy, crucial for delivering high-quality, accessible mental healthcare at scale. You will be responsible for designing analytical frameworks, developing data science products, and uncovering insights to power Headspace’s mission of providing 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 define and track key marketplace metrics, including access (e.g., time-to-appointment), utilization, and network health.
- Define and standardize clinical and coaching outcome metrics (e.g., PHQ, GAD, PSS) and ensure they are reliably captured and reported.
- Lead the development of end-to-end measurement frameworks for care journeys, ensuring high data quality and instrumentation completeness.
- Apply causal inference and statistical modeling to evaluate engagement, and long-term member outcomes.
- Partner with stakeholders to translate outcome insights into product, clinical, and operational improvements.
- Build and scale data products, forecasting pipelines, and decision-support tools that enable self-service insights and automation.
- Collaborate with Data Engineering and BI to define robust data models, metric definitions, and reporting layers.
- Translate complex models into intuitive dashboards and tools for business and operational stakeholders.
- Act as a thought leader in forecasting, experimentation, and decision science, raising the bar for analytical rigor across the organization and partner on the ROI dashboards.
- Drive new uses of AI in analytics and forecasting.
- Mentor and develop data scientists and analysts, strengthening capabilities in communication, stakeholder influence, and technical execution.
- Communicate complex findings clearly to executive and non-technical audiences, driving alignment and action as member of the Care marketplace leadership team.
What you will bring:
Required Skills:
- 8+ years of well-rounded analytics and data science experience, ideally with exposure to Digital Health, high-growth SaaS, and/or Mental Health industries in rapid growth environments.
- 6+ years of experience successfully partnering directly with executive leadership and product leaders, showcasing the ability to align analytics, data science with strategic goals.
- Proven experience building and deploying forecasting models, optimization solutions and decision frameworks in complex, real-world environments.
- Strong 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.
- 4+ years of progressive experience in healthcare analytics (preferred).
- 7+ years of expertise in big data technologies (e.g., Redshift, S3, Databricks, Datalakes, Spark).
- Advanced skills in SQL and Python, with Looker, Tableau, Amplitude, Statsig for event-based deep dives and advanced analytics also preferred.
- Bachelor's or master's degree in computer science, statistics, mathematics, or a related quantitative field.