Data Scientist

Role & responsibilities

Role Overview:

• Design, develop, and implement Machine Learning, AI, and Generative AI solutions that support measurable business outcomes across the disability insurance value chain, including fraud detection, duration modelling, risk scoring, and next-best-action recommendations.
• Work closely with business stakeholders, actuarial teams, claims teams, and senior data scientists to understand business problems and translate them into practical analytics and ML use cases.
• Contribute across the analytics lifecycle, including problem framing, exploratory data analysis, feature engineering, model development, validation, deployment support, and performance monitoring.
• Support technical problem solving within project teams and share knowledge with analysts and junior team members where required.
• Assist in developing experimentation frameworks, analytical approaches, and reusable assets that improve model quality and accelerate AI adoption.
• Follow responsible AI principles, model governance standards, data privacy requirements, and regulatory guidelines while developing analytics solutions.
• Design, develop, and optimize ML models for claim segmentation, risk scoring, and outcome prediction
• Build NLP pipelines for medical records, claim notes, and unstructured documents
• Perform feature engineering using structured and unstructured claims data
• Conduct model validation, performance tuning, bias detection, and explainability analysis
• Support model deployment, monitoring, retraining, and drift detection
• Collaborate with business and actuarial & claims teams to translate objectives into ML use cases
• The candidate will be part of an agile analytics team that combines diverse skills, backgrounds, and perspectives to solve complex business problems.
• A suitable candidate should have 4+ years of applied data science experience, preferably with exposure to healthcare, insurance, disability claims, or other regulated domains.

Preferred candidate profile