Head of Data

About the Company:

Octave is a modern behavioral health practice creating a new standard for care delivery that’s both high-quality and accessible. With in-person and virtual clinics in multiple states, the company offers evidence-based individual, couples, and family therapy, while pioneering relationships with payers to make care more affordable through insurance. By raising the bar on how care is delivered and how providers are supported, we are building a sustainable system that values equity, affordability, and effectiveness.

About the Role:

As Head of Data, you will own our end-to-end data function: analytics, data engineering, and data science. You will set the vision and roadmap for how we use data and AI/ML across the company, ensure our infrastructure is reliable and scalable, and lead the development of product- and business-facing AI applications. This role is both strategic and operational: you’ll partner with executives to shape company direction, while also ensuring your teams deliver reliable pipelines, actionable insights, and production-ready models. You’ll also be a team builder, responsible for developing current talent and hiring externally to close skill gaps in critical areas like advanced data science, ML engineering, and data governance.

Management Responsibilities: 

• Develops, coordinates, and implements  systems, policies, procedures, and productivity standards.
• Provide leadership and guidance to the team, ensuring the achievement of goals and objectives.
• Foster a positive and collaborative work environment.
• Oversee the planning, execution, and completion of projects and initiatives within the team.
• Establish and monitor operational processes and workflows to enhance efficiency and productivity.
• Streamline operational processes, enhance efficiency, and improve overall organizational performance. 
• Implement best practices, monitor key performance indicators (KPIs), and develop strategies to achieve operational excellence.
• Ensures a safe, secure, and compliant work environment.
• Accomplishes staff results by communicating job expectations; planning, monitoring, and appraising job results.
• Build and manage a high-performing team, including hiring, training, and development.
• Provide leadership to the team, including setting goals, providing guidance, and ensuring the team's overall success.
• Set performance expectations and goals for team members. Conduct regular performance evaluations, provide feedback, and address performance issues. 
• Identify skill gaps within the team and develop strategies for filling those gaps. Support employee development through training, mentoring, and coaching. Identify high-potential employees and create succession plans.

Responsibilities Include:

• Strategy & Leadership
• Define and drive the company-wide data & AI/ML vision, aligned with business and product strategy.
• Partner with executives across Product, Engineering, Growth, and Finance to ensure data informs key decisions and creates competitive advantage.
• Evangelize data culture — making data and AI central to how we operate and build.
• Data Infrastructure & Governance
• Oversee pipelines, warehouse, and infrastructure for reliability, observability, and scale.
• Establish a single source of truth for KPIs and reporting.
• Implement governance for data quality, security, and compliance.
• Analytics & Decision Intelligence
• Lead analytics team to deliver insights that drive product, growth, and operations.
• Scale self-serve analytics adoption while maintaining consistency and quality.
• Build frameworks for experimentation (A/B testing, causal inference).
• AI/ML Innovation
• Launch and scale high-impact AI/ML initiatives, from pilots to production.
• Build the foundation for ML operations: monitoring, retraining pipelines, feature store.
• Ensure responsible AI practices around bias, fairness, and explainability.
• Explore emerging AI capabilities (LLMs, generative AI) to keep us ahead of the curve.
• Team Building & Talent Development
• Lead, mentor, and develop a growing team of analysts, engineers, and scientists.
• Identify gaps and hire externally for critical expertise (e.g., ML engineers, senior scientists).
• Define career ladders and growth paths to retain and motivate top talent.
• Build the company’s reputation as a top destination for data and AI talent.

Required Qualifications:

• 8+ years of experience in data analytics/data science, with 4+ years in a leadership role scaling teams and delivering cross-functional impact.
• Expertise with an