Lead Data Scientist - Hybrid

About the role

Manulife is seeking a Lead Data Scientist in Boston to develop advanced analytics and AI solutions that improve underwriting decisions, expand automation and deliver measurable business value. The role leads complex analytical work from problem definition through model development, implementation and ongoing enhancement, and combines hands-on modelling with technical direction, mentoring and stakeholder communication. It is a hybrid position.

Key responsibilities

• Partner with underwriting, business, product and technology stakeholders to identify and prioritize data science opportunities.
• Lead data science projects from problem definition and data exploration through modeling, evaluation, implementation and enhancement.
• Develop statistical and machine-learning models suited to the business problem, available data and intended use.
• Analyze large and complex datasets to identify patterns and support business decisions.
• Define model-evaluation approaches so solutions are accurate, interpretable, stable and aligned with business objectives.
• Evaluate new data sources, analytical methods and third-party solutions through structured analysis and experimentation.
• Work with data, machine-learning and software engineers to implement solutions in production, monitor model performance and recommend improvements.
• Prepare technical documentation for implementation, validation, governance and model management.
• Provide technical direction, review analytical work and mentor data scientists and other contributors.

Required profile

• Bachelor's or advanced degree in Statistics, Mathematics, Data Science, Computer Science, Engineering, Actuarial Science, Economics or a related quantitative field.
• 8 years of experience applying statistics, machine learning or predictive analytics to complex business problems.
• Demonstrated experience developing analytical solutions from concept through production implementation and monitoring.
• Experience leading analytical workstreams and giving technical guidance to other data scientists.
• Solid experience in life insurance underwriting, automated underwriting, risk selection or related insurance analytics.

Required skills

• Strong knowledge of statistical modeling, machine learning, model evaluation and experimental design.
• Proficiency in Python or R and SQL, with experience on large and complex datasets.
• Technical documentation, problem-solving and communication skills.
• Asset: cloud-based analytics platforms, model governance, external data evaluation or third-party model assessment; familiarity with actuarial concepts or an actuarial designation is an asset but not required.

What we offer

• Expected salary range of $127,330 to $236,470 USD, with incentive compensation tied to performance.
• Benefits including health, dental, mental health, vision, disability, life and AD&D insurance, retirement savings plans and paid time off.
• A flexible, inclusive environment with growth and learning opportunities.