Responsibilities: People management
- Oversee workforce planning, budgeting, and talent roadmap for the AI & Model team.
- Attract, onboard, and retain top-tier AI/ML, actuarial analytics, and data science talents.
- Define and communicate team and individual KPIs/KRAs, performance expectations, and delivery standards.
- Lead performance management cycles, providing continuous feedback, coaching, and development.
- Identify skill gaps, design training pathways, and build technical and leadership capabilities for team members.
- Recognize contributions and foster a high-performance, innovation-driven culture.
- Build a sustainable talent pipeline within the function.
- Act as a role model, promoting collaboration, ethics, experimentation, and ownership.
- Communicate and clarify HR policies and initiatives to team members.
Build Team and Capabilities
- Build and lead an integrated team of AI engineers, ML scientists, data analysts, actuaries, model validators, and MLOps engineers.
- Establish technical standards, seniority levels, competency frameworks, and evaluation mechanisms for the team.
- Introduce advanced AI/ML capabilities (machine learning, deep learning, NLP, computer vision, generative AI, predictive modeling) tailored to insurance use cases.
- Implement modern tech stacks and platforms: distributed computing, cloud-based ML pipelines, model deployment frameworks, feature stores, real-time scoring engines, etc.
- Set measurable KPIs with direct linkage to business value (loss reduction, conversion uplift, fraud detection rate, automation rate, health scoring accuracy, etc.).
- Cultivate a culture of innovation, experimentation, agile collaboration, and product-centric thinking.
Cooperate with Business and Create Data Products
- Build strong partnerships with underwriting, actuarial, claims, health service, digital, marketing, and operations teams to accelerate AI adoption.
- Collaborate with business stakeholders to identify high-impact AI use cases and translate objectives into data and model requirements.
- Lead the design, development, and deployment of AI-powered insurance products such as:
Dynamic pricing & risk scoring models
- Automated claims adjudication
- Health risk prediction models
- Fraud detection engines
- Personalized customer recommendations
- Churn prediction and retention models
- Digital sales conversion optimization models
- Evangelize AI within and outside the organization, promoting a data-driven and model-driven culture.
- Ensure AI solutions are explainable, compliant, ethical, and aligned with insurance regulatory requirements. .
Manage and Drive Projects to Success
- Act as a product leader, connecting business requirements with technical model development.
- Establish cross-functional squads for each AI initiative, ensuring alignment on shared KPIs and outcomes.
- Implement agile and iterative delivery practices to accelerate model development and experimentation.
- Translate business strategies into model blueprints, resource plans, and development roadmaps.
- Conduct post-mortem reviews, track root causes, and continuously improve AI delivery processes.
- Ensure AI/ML models are robust, well-validated, monitored, and integrated seamlessly into business workflows and digital channel.
- Oversee MLOps and model lifecycle management, ensuring reliability, scalability, and version control for all deployed models.
Requirements: Education
- Master’s or Doctoral degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, Actuarial Science, or a quantitative discipline.
Relevant experience
- 12+ years of experience in Data Science, Machine Learning, Applied AI, or similar fields.
- Minimum 8+ years managing AI/ML teams or advanced analytics units.
- Proven experience developing and deploying AI/ML models in production, preferably within insurance, health-tech, or financial services.
- Experience in building data products and AI-driven business solutions.
- Demonstrated ability to drive large-scale AI initiatives, reshape organizational ways of working, and embed AI into business operations.
- Strong experience with Agile development frameworks and leading AI squads.
- Experience leading or participating in AI labs, model governance committees, or innovation centers.
- Hands-on experience with ML systems used in digital channels, real-time scoring, mobile/online personalization, automated decisioning, etc.
- Excellent understanding of digital, insurtech, and AI trends, including cloud AI, generative AI, model governance, and ethical AI.
- In-depth knowledge of current and emerging AI technologies relevant to insurance, including health analytics, risk modeling, and fraud analytics.
HOW TO APPLY: Please send your CV to the consultant in charge:
Ms. Anh Duong
Email: anh.duong@ev-search.com
All applications will be considered without regard to race, color, religion, sex (inclusing pregnancy and fender identity), national origion, political affiliation, sexual orientation, mariatal status, disability, genetic information, age, membership in an employee organization, parental status, military service or other nonmerit factor.
