Product Manager - AI & Data Analytics
Drive product vision and roadmap for customer-facing AI/ML models, data products, and analytics features. Work directly with B2B SaaS customers to co-develop solutions, translating technical capabilities into business value.
Product Strategy & Vision
- Own the product vision and strategic roadmap for external, customer-facing AI/ML models, data products, and analytics features
- Engage directly with strategic customers and design partners to understand their needs, validate roadmaps, and co-develop new features
- Define, measure, and communicate product success using metrics that correlate with customer value and SaaS business metrics (adoption, retention, ARR expansion)
- Partner with UX, Data Science, and Sales Engineering to create impactful data visualizations and product demos
Product Execution & Delivery
- Define clear, testable requirements (epics and user stories) based on customer feedback, market analysis, and strategic priorities
- Write precise, detailed specifications for complex data processes, transformation logic, and aggregation rules
- Partner with Product Marketing, Sales, and Customer Success to develop launch plans, sales collateral, and communication plans for new features
Technical Analysis & Enablement
- Conduct product-related data analysis, validate data assets, and prove/disprove hypotheses
- Act as the primary translator between customer requirements and data engineering
- Work closely with data scientists to define requirements for AI/ML-driven features
Requirements
- 3-5+ years of relevant experience in product management, data analytics, or BI development
- Strong ability to connect complex technical features to customer value, user needs, and business outcomes
- Experience working directly with customers or stakeholders to gather requirements and manage feedback loops
- Excellent communication and data storytelling skills
- Demonstrated ability to manage a backlog, make trade-offs, and align teams on priorities
- Solid SQL fundamentals for data exploration and analysis
- Experience with modern BI platforms (Tableau, Looker, Power BI, Sigma)
- Strong functional understanding of data transformation techniques (aggregation, string manipulation, type casting)
Nice-to-Haves
- Experience with modern data stack tools (Snowflake, Fivetran, DBT, Sigma)
- Domain expertise in B2B SaaS verticals such as Field Services or Building Services
- Familiarity with scripting languages (R or Python) for data analysis
- Exposure to the AI/ML lifecycle or production machine learning models
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