Product manager- Insurance Data Solutions KE

Smart Applications International Limited

Job Location:

Nairobi - Kenya

Monthly Salary: Not Disclosed

Experience Required: 5years

Posted on: Yesterday

Vacancies: 1 Vacancy

Job Summary

Smart Applications International is a leading ISO-certified ICT solutions provider delivering a wide range of world-class technological solutions. Fondly known as Smart within the healthcare industry the company was founded to provide innovative secure and high-tech solutions across Africa the Islands and beyond. Smart Applications stay ahead through constant research and innovation.

Title: Product manager- Insurance Data Solutions

Reports to: Group Director Insurance Business

Based in: Kenya (or as maybe assigned from time to time)

Job Purpose:
The Product Manager Insurance Data Solutions will lead the development commercialization and adoption of all insurance-facing data products across the group harnessing data from MediSmart and SmartInsure as well as any other product to leverage this into products such as SmartAnalytics AI Smart Detect and other Smart data products. This role combines strategic business leadership advanced analytics expertise and product innovation to drive revenue optimize customer outcomes and position Smart as a market leader in insurance data solutions across all countries of operation.

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 Smarts 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:

Bachelors 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.
Masters degree or relevant professional certification is highly desirable.
812 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

Revenue Growth by X%/ KES Direct revenue generated from new and existing insurance data products across all markets annually.
Product Adoption & Retention Percentage of active usage and retention rates of insurance data solutions among clients and internal teams.
Actuarial Accuracy & Intervention Impact Reduction in customer loss ratios or claims inaccuracies through improved data-driven. interventions and actuarial modeling.
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.
Market Expansion & Geographic Coverage Successful rollout and standardization of insurance data products across all operational countries measured by adoption rates and market penetration.

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