About the Role
Lead the development and execution of data science initiatives that support product innovation and business growth. Oversee model design, mentor team members, and align analytical efforts with strategic goals.
Responsibilities
- Direct the creation and deployment of machine learning models to solve business challenges
- Collaborate with engineering teams to integrate models into production systems
- Define success metrics and evaluate impact of data-driven solutions
- Mentor data scientists in technical and professional development
- Translate business questions into analytical frameworks
- Ensure data quality and integrity across pipelines
- Lead A/B testing design and interpretation of results
- Communicate findings to technical and non-technical stakeholders
- Drive best practices in statistical analysis and model validation
- Prioritize data science projects based on business value
- Manage timelines and deliverables for analytical initiatives
- Stay current with advancements in machine learning and data science methods
- Support data governance and ethical use of predictive models
- Partner with product teams to inform roadmap decisions
- Develop forecasting models to anticipate user behavior
- Optimize algorithms for performance and scalability
- Conduct exploratory data analysis to uncover insights
- Establish documentation standards for modeling workflows
- Coordinate with data engineering on feature store development
- Evaluate third-party data sources for integration potential
- Lead root cause analysis for product performance issues
- Design segmentation strategies to personalize user experiences
- Facilitate knowledge sharing across analytics functions
- Implement monitoring systems for model performance decay
- Balance innovation with operational reliability in model pipelines
Nice to Have
- PhD in a quantitative discipline
- Experience in healthcare or mental health technology
- Leadership in scaling data science functions
- Publications or presentations in data science or machine learning venues
- Open-source contributions related to data science tools
- Experience with natural language processing applications
- Background in causal machine learning methods
- Familiarity with regulatory requirements for algorithmic systems
- Track record of building data science teams from the ground up
- Experience mentoring through periods of organizational growth
Compensation
Competitive salary and equity package
Work Arrangement
Remote-friendly with team coordination across time zones
Team
Cross-functional team integrating data science, engineering, and product
Our Impact
We focus on improving access to mental health care through technology-enabled services. Our data science work directly informs how providers are matched with patients and how care pathways are optimized.
Growth Opportunities
This role offers the chance to shape the future of analytics in a high-growth environment. You will define best practices, grow the team, and influence product strategy at a strategic level.
Available for qualified candidates
