Senior Data Product Manager

Who Connecteam is:

Connecteam is the leading platform for managing deskless teams, trusted by over 80,000 businesses worldwide.
We built Connecteam for real operators - the people running shifts, jobs, and teams across stores and sites. The kind of work that doesn’t happen behind a desk, and doesn’t have time for messy spreadsheets, scattered group chats, or tools that don’t talk to each other.
Connecteam brings daily operations and team communication into one intuitive app - from hiring and scheduling to training, tasks, and day-to-day coordination. It gives teams the clarity and control to run the day, shift after shift, job after job.
Backed by $220M+ from Insights Partners, Stripes, and Tiger Global, Connecteam is rapidly expanding worldwide - empowering frontline teams to work smarter, stay connected, and operate with greater efficiency.

About The Role

Connecteam is looking for an experienced Data Product Manager with a strong Data Science and Analytics background to own and lead data driven solutions.
In this role, you will define and drive the vision, strategy, and execution of data and analytics products that support our Marketing, Growth, and Acquisition teams. You will operate at the intersection of business, analytics, data science, and AI, translating marketing challenges and business questions into scalable data products, clear KPIs, and measurement frameworks that improve acquisition efficiency, ROI, and long-term revenue growth.
You will lead cross-departmental initiatives, partner closely with Marketing leaders, Data Scientists, Data Engineers, Analytics teams, and Product Managers, and ensure that advanced modeling, analytics, and AI capabilities are deeply embedded into day-to-day marketing decision-making.

Key Responsibilities

Marketing Data Product Ownership

• Own the vision, roadmap, and delivery of Marketing Data Science and Analytics products
• Align initiatives with business goals such as acquisition efficiency, ROI optimization, revenue growth, and funnel performance.
• Act as the single point of ownership for marketing-related data, analytics, and data science products across teams.
• Define data requirements, metrics, and success criteria for new initiatives, including identifying gaps in existing data.
• Collaborate with Data Engineers and Analytics Engineers to design scalable data pipelines, data models, and semantic layers that support analytics, experimentation, and advanced modeling.
• Prioritize initiatives based on business impact, scalability, data maturity, and clarity of success metrics.

Business Analytics, Data Science & AI–Driven Marketing Optimization

• Define and own the business logic behind marketing KPIs, ensuring clear, consistent, and trusted metrics across teams.
• Work closely with stakeholders to understand what needs to be measured, why and how.
• Lead data science, analytics, and AI initiatives that optimize marketing performance
• Own and evolve core marketing models including attribution, MMM, LTV prediction.
• Define success metrics and measurement frameworks for models, experiments, and AI-driven decisions.
• Drive experimentation frameworks (A/B tests, geo-experiments, uplift modeling) to continuously improve performance and decision quality.
• Design and deploy AI-powered and agentic solutions to automate and scale marketing workflows such as budget allocation, campaign optimization, and creative testing.
• Ensure solutions are production-ready, measurable, explainable, and actionable for business stakeholders.
• Translate complex model outputs into clear, trusted insights for business users.

Experience & Skills

• 5+ years of experience in Data Product Management, Data Science Product, Analytics Product, or similar roles in a tech or SaaS environment.
  Strong understanding of business analytics, KPI definition, and metrics design, alongside marketing data science, performance marketing, and growth analytics.
  Proven experience owning data and analytics products end-to-end, from business problem definition and measurement strategy through strategy, development, and production.
• Hands-on experience working with data scientists, analytics engineers, data engineers, and BI/analytics teams.
• Ability to translate business questions into analytical frameworks, metrics definitions, dashboards, and experimentation plans.
• Familiarity with attribution, MMM, LTV modeling, experimentation, and optimization frameworks.
• Strong communication skills and stakeholder management across technical and non-technical teams, with the ability to communicate insights clearly to business leaders.

Advantages:

• Experience building or productizing AI-powered or agentic systems.
• Background in performance marketing, growth teams or marketing platforms.
• Experience in fast-growing or high-scale startups.
• Strong understanding of experimentation frameworks.