Product manager- Insurance Data Solutions

Smart Applications International is looking for a product manager to join its team.

Job Description

1. Product Strategy & Revenue Growth

• Define and own the insurance data product roadmap across all platforms and regions.

• Identify market needs, gaps and opportunities to develop innovative, revenue-generating data products.

• Drive adoption and monetization of insurance data solutions across internal teams and external clients.

• Translate complex data insights into actionable business strategies that increase revenue and reduce customer loss ratios.

2. Technical Leadership & Collaboration

• Partner with Actuaries, SmartInsure, MediSmart and AI teams to define Smart data products that aid/resolve challenges in refining pricing, claims, and risk models, ensuring Smart’s analytics influence decision-making.

• Build and scale advanced AI/ML-driven insurance solutions that automate interventions, improve accuracy, and enhance operational efficiency.

• Champion integration of predictive and prescriptive analytics into all insurance platforms.

3. Stakeholder & Cross-Functional Engagement

• Act as a strategic advisor to executives, presenting data-driven insights to influence business decisions.

• Work closely with sales, operations and technology teams to ensure product adoption and commercial success.

• Collaborate across countries to standardize and roll out insurance data products across the group footprint.

4. Governance & Operational Excellence

• Establish robust analytics governance, data stewardship and quality frameworks.

• Track and report KPIs aligned with business outcomes, including revenue, product adoption, actuarial accuracy, AI integration and market expansion.

• Ensure scalability, sustainability and compliance of all insurance data solutions.

Requirements

Required Qualifications & Experience:

• Bachelor’s degree in Statistics, Data Science, Actuarial Science, Economics, Computer Science, or related field.

• Strong business acumen, entrepreneurial mindset to drive revenue and profitability from insurance data solutions.

• Master’s degree or relevant professional certification is highly desirable.

• 8–12 years in analytics, product management, or data science, preferably in health insurance, healthcare, or financial services.

• Proven experience in building revenue-centric data products and managing high-performing data business.

• Strong understanding of insurance operations, actuarial modeling, and emerging AI/ML applications.

Key Competencies & Technical Skills

• Strategic and commercial acumen with a results-driven mindset.
  

• Ability to translate complex analytics into executive-level insights.
  

• Exceptional stakeholder management and cross-functional influence.
  

• Innovation-focused, with a proven track record of product commercialization.
  

• Integrity, attention to data governance, and compliance.
  

• Advanced analytics, statistical modeling, and predictive modeling.
  

• Experience with BI tools (Power BI, Tableau, Looker) and data visualization.
  

• Proficiency in SQL and programming languages (Python, R).
  

• Familiarity with cloud platforms, data warehouses, APIs, and scalable analytics architecture.

Key KPIs

1. Revenue Growth by X%/ KES – Direct revenue generated from new and existing insurance data products across all markets annually.
   

2. Product Adoption & Retention – Percentage of active usage and retention rates of insurance data solutions among clients and internal teams.
   

3. Actuarial Accuracy & Intervention Impact – Reduction in customer loss ratios or claims inaccuracies through improved data-driven. interventions and actuarial modeling.
   

4. AI/ML Solution Deployment – Number and impact of AI/ML-driven features successfully deployed across insurance platforms, measured by automation effectiveness, predictive accuracy, or operational efficiency.
   

5. Market Expansion & Geographic Coverage – Successful rollout and standardization of insurance data products across all operational countries, measured by adoption rates and market penetration.