Senior Data Product Manager (AI Insurance SaaS)
EvolutionIQNew York, NYPosted 26 March 2026
Tech Stack
Job Description
About Us: EvolutionIQ’s mission is to deliver state of the art technology that helps insurance claims teams make claims handling more accurate, fair, and efficient, so that more people impacted by injury or illness can continue their lives with dignity and stability. We are currently experiencing massive growth and to accomplish our goals, we are hiring world-class talent who want to help build and scale internally, and transform the insurance space. Our team is our #1 priority, and we have been named one of Inc.’s Best Workplaces 3 years in a row and Built In’s Best Places to work in 2025 and 2026!
We’re looking for a Senior Data Product Manager to own the strategy, execution, and evolution of data-driven products across our platform. This is a highly impactful role working closely with engineering, data science, and business stakeholders to turn complex data and analytics into products that drive real customer value.
In This Role, You Will:
Own data products through their full lifecycle: discovery, definition, delivery, launch, and continuous improvement.
Define product vision and strategy for data-driven features, analytics platforms, or AI/ML powered capabilities.
Translate customer and business needs into clear product requirements, PRDs, and roadmaps.
Partner closely with Engineering, Data Science and other stakeholders to scope, prioritize, and deliver high-impact solutions.
Prioritize ruthlessly based on customer value, business impact, and technical feasibility.
Drive execution to ship high-quality, scalable data products.
Work with stakeholders across the company (GTM, Ops, Leadership, Clients) to ensure alignment and adoption.
Define success metrics and use data to evaluate product performance and guide iteration.
Help shape how data, analytics, and AI are turned into repeatable, scalable product capabilities.
Requirements:
Actuarial or data science background strongly preferred
3–5+ working directly for a large insurance carrier or consulting in an actuarial or analytical role or relevant experience in B2B SaaS
Strong ability to work across technical and non-technical teams and communicate clearly in both directions.
Ability to define, launch, and iterate on products used by real customers.
Ability / experience building data products, analytics platforms, or ML/AI-driven features.
Comfortable working in ambiguous, fast-moving environments with a high degree of ownership.
Strong written and verbal communication skills. A collaborative, feedback-driven working style.
Experience in insurance, insurtech, or regulated data-heavy industries is a big plus, but not required.
Experience partnering closely with data science or data engineering teams.
Experience building data platforms,or analytics products or machine learning or decisioning systems is a big plus, as well as complex workflows or enterprise customers
Work-life, Culture Perks:
Compensation: The base salary range is $200-220K, with flexibility depending on a candidate’s background and experience. An annual bonus plan and company equity plan (RSUs) are also included in our compensation package.
Well-Being: Medical, dental, vision, short long-term disability, life insurance and ADD, and 401k matching. Additional family, wellness, and pet benefits.
Home Family: Paid time off and sick leave, 100% paid parental leave (16 weeks for primary caregivers and 12 weeks for secondary caregivers). We offer a flexible schedule for new parents returning to work.
Office Life: Catered lunches, happy hours, pet-friendly spaces, and monthly technology stipend.
Growth Training: $1,000/year for each employee for professional development, as well opportunities for tuition reimbursement.
Sponsorship: We are open to sponsoring candidates currently in the U.S. who need to transfer their active visa. Please check with our Recruiting team if your visa is applicable for transfer.
EvolutionIQ appreciates your interest in our company as a place of em ... (truncated, view full listing at source)
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