Interim Head of Data Science & Analytics

Ports North; Alameda (CA); On-site; USD 180,000 - 300,000; Full time

Job summary

Ports North is seeking an experienced interim leader to head Data Science and Product Analytics, guiding a high-performing team through a leadership transition. You will own the data platform and analytics roadmap, oversee ML deployment, and translate data into growth strategies while collaborating with executives across Product, Design, Engineering, Marketing, and Business units.

The role requires a proven track record in data science leadership, product analytics, and fast execution to

Qualifications

• Proven leadership in data science, analytics, or product analytics within tech, pharma, medical device, or healthcare products.
• Progressive background across data analytics, data science, and product management roles.
• Demonstrated interim or transitional leadership-able to step in quickly to execute, stabilize, and manage through change.
• Strong Product Owner track record defining strategy and roadmaps for data platforms and analytics ecosystems.
• Hands-on knowledge of ML deployment, product analytics tooling, and experimentation frameworks.
• Excellent stakeholder management and communication skills.

Responsibilities

• Lead and develop a high-performing team of data scientists and product analysts.
• Serve as Product Owner for the core data platform, defining strategy, priorities, and roadmap execution.
• Own the AI, data science, and analytics roadmap, including customer-facing and AI-powered capabilities.
• Oversee the deployment, monitoring, and improvement of production machine learning models.
• Serve as Product Owner for the product analytics ecosystem, ensuring scalable measurement and actionable insights.
• Champion a data-driven culture through experimentation, best practices, and evidence-based decision making.
• Define and monitor product and divisional performance metrics aligned to business goals.
• Advise Product, Design, Engineering, Marketing, and Business leaders, translating data into growth strategies.
• Mentor team members and build organizational capability in data science, analytics, and AI.

Job description

Interim Head of Data Science & Product Analytics

About the Opportunity

Our client, a growing organization in the medical technology and healthcare products space, is seeking an experienced interim leader for their Data Science and Product Analytics function. This role ensures continuity during a leadership transition-keeping the team productive and aligned while maintaining momentum. The ideal consultant can step in immediately to execute against an established roadmap and manage a high-performing team without disruption.

Key Responsibilities

• Lead and develop a high-performing team of data scientists and product analysts.
• Serve as Product Owner for the core data platform, defining strategy, priorities, and roadmap execution.
• Own the AI, data science, and analytics roadmap, including customer-facing and AI-powered capabilities.
• Oversee the deployment, monitoring, and improvement of production machine learning models.
• Serve as Product Owner for the product analytics ecosystem, ensuring scalable measurement and actionable insights.
• Champion a data-driven culture through experimentation, best practices, and evidence-based decision making.
• Define and monitor product and divisional performance metrics aligned to business goals.
• Advise Product, Design, Engineering, Marketing, and Business leaders, translating data into growth strategies.
• Mentor team members and build organizational capability in data science, analytics, and AI.

Required Skills & Experience

• Proven leadership in data science, analytics, or product analytics within tech, pharma, medical device, or healthcare products.
• Progressive background across data analytics, data science, and product management roles.
• Demonstrated interim or transitional leadership-able to step in quickly to execute, stabilize, and manage through change.
• Strong Product Owner track record defining strategy and roadmaps for data platforms and analytics ecosystems.
• Hands-on knowledge of ML deployment, product analytics tooling, and experimentation frameworks.
• Excellent stakeholder management and communication skills.