Product Manager, Data Analytics

About the role

The role sits at the intersection of data science, software engineering, and business strategy, translating analytical insights into scalable systems and partnering with technical teams to operationalize machine learning models into production-grade applications.

Responsibilities

• Collaborates with business, analytics, and engineering teams to define the vision, strategy, and long-term roadmap for data and machine learning products.
• Translates complex pricing, forecasting, and operational needs into clear product requirements, user stories, and acceptance criteria.
• Led prioritization across competing business and technical needs, managing backlogs and release plans.
• Serves as product spokesperson and subject matter expert for analytics capabilities across the enterprise.
• Works directly with data scientists to understand and refine model outputs, feature relevance, performance metrics, and constraints.
• Applies strong technical knowledge of machine learning workflows, pipelines, APIs, and model monitoring to guide product direction and evaluate trade-offs.
• PARTNERS WITH THE SENIOR SOFTWARE ENGINEER – DATA & ANALYTICS PRODUCTS TO OPERATIONALIZE MODELS INTO USER-FACING APPLICATIONS AND ENTERPRISE SYSTEMS.
• Ensures all ML-driven product features emphasize explainability, compliance, and reliability.
• Defines and tracks key KPIs (e.g., model accuracy, revenue lift, adoption, system reliability) to measure product performance and business impact.
• Establishes a structured cadence for reviewing KPIs with cross-functional partners and initiating corrective actions or enhancements.
• DRIVES SUCCESSFUL DELIVERY OF MILLENNIA, MVP RELEASES, AND PRODUCT ITERATIONS.
• LEADS RETROSPECTIVES AND DRIVES CONTINUOUS IMPROVEMENT OF ANALYTICS WORKFLOWS, MODEL GOVERNANCE, AND PRODUCT EXECUTION PROCESSES.
• ACTS AS THE BRIDGE BETWEEN DATA SCIENTISTS, SOFTWARE ENGINEERS, IT, PRICING, AND OPERATIONS TEAMS.
• Facilitates workshops, demos, feedback sessions, and cross-functional updates to maintain alignment and transparency.
• COMMUNICATES COMPLEX ANALYTICAL CONCEPTS IN A CLEAR, BUSINESS-RELEVANT MANNER FOR STAKEHOLDERS AT ALL LEVELS.
• SUPPORTS CHANGE MANAGEMENT, TRAINING, AND ADOPTION FOR NEW ANALYTICS CAPABILITIES ACROSS THE ORGANIZATION.

Requirements

• Bachelor’s degree required; degree in Business, Computer Science, Engineering, Analytics, Economics, or related field preferred.
• 5 plus years of experience in Product Management, Technical Program Management, or Engineering, with a focus on data, analytics, or platform development.
• Strong technical working knowledge of machine learning models, data pipelines, model deployment workflows, and APIs—with hands-on experience partnering with data scientists and engineers.
• Demonstrated ability to integrate machine learning driven features into end-to-end production systems and evaluate model performance.
• Proficiency with SQL, analytics environments, and BI tools (Power BI, Tableau, etc.).
• Proven experience with Agile methodologies, backlog management, sprint execution, and iterative product delivery.
• Experience defining and managing program-level KPIs, establishing review cadences, and leading data-driven decision processes.
• Experience in Revenue Management, pricing optimization, forecasting, yield management, or similar analytical domains (real estate, hospitality, travel, etc.).
• Excellent verbal and written communication skills with ability to translate between technical and non-technical stakeholders.