Lead Data Scientist - Hybrid

Manulife John Hancock; Boston (MA); On-site; USD 150,000 - 200,000; Full time

Job summary

Manulife John Hancock is seeking a Lead Data Scientist to develop advanced analytics and AI solutions that enhance underwriting decisions and automation. You will lead problem definition, model development, and production deployment while guiding a team of data scientists and collaborating with underwriting, product, and technology stakeholders.

This hands-on role emphasizes scalable, interpretable models, technical leadership, and clear communication of recommendations to both technical and

Qualifications

• 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.
• Strong knowledge of statistical modeling, machine learning, model evaluation, and experimental design.
• Proficiency in Python or R and SQL, with experience working with large and complex datasets.
• Demonstrated experience developing analytical solutions from concept through production implementation and monitoring.
• Experience leading analytical workstreams and providing technical guidance to other data scientists.

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 using techniques appropriate to the business problem, available data, and intended use.
• Analyze large and complex datasets to identify patterns, generate insights, and support business decisions.
• Define model-evaluation approaches and ensure 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.
• Collaborate with data engineers, ML engineers, software engineers, and technology teams to implement analytical solutions in production.
• Monitor model performance, investigate unexpected outcomes, and recommend improvements as data and business conditions evolve.
• Prepare clear technical documentation to support implementation, validation, governance, and ongoing model management.
• Provide technical direction, review analytical work, and mentor data scientists and other analytical contributors.

Skills

Statistics

Data science

Python/R

SQL

Communication

Leadership

Problem-solving

Actuarial knowledge

Education

Bachelor's degree in Statistics or related

Master's degree in related field

Actuarial designation (asset)

Tools

Cloud platforms

Model governance

External data evaluation

Third-party model assessment

SQL databases

Job description

The Opportunity

We are seeking a Lead Data Scientist to develop advanced analytics and AI solutions that improve underwriting decisions, expand automation, and deliver measurable business value.

The successful candidate will lead complex analytical work from problem definition through model development, implementation, and ongoing enhancement. This role requires strong data science expertise, solid life insurance underwriting knowledge, and the ability to provide technical direction across projects.

Job Summary

The Lead Data Scientist is responsible for developing and delivering statistical and machine-learning solutions for automated underwriting and related business problems. The role translates complex business needs into rigorous analytical approaches and ensures that solutions are accurate, interpretable, scalable, and practical for business use.

This is a hands-on role that also provides technical direction, reviews analytical work, mentors other data scientists, and communicates recommendations to technical and business stakeholders.

Position 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 using techniques appropriate to the business problem, available data, and intended use.
• Analyze large and complex datasets to identify patterns, generate insights, and support business decisions.
• Define model-evaluation approaches and ensure 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.
• Collaborate with data engineers, machine-learning engineers, software engineers, and technology teams to implement analytical solutions in production.
• Monitor model performance, investigate unexpected outcomes, and recommend improvements as data and business conditions evolve.
• Prepare clear technical documentation to support implementation, validation, governance, and ongoing model management.
• Provide technical direction, review analytical work, and mentor data scientists and other analytical contributors.

Qualifications

• 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.
• Strong knowledge of statistical modeling, machine learning, model evaluation, and experimental design.
• Proficiency in Python or R and SQL, with experience working with large and complex datasets.
• Demonstrated experience developing analytical solutions from concept through production implementation and monitoring.
• Experience leading analytical workstreams and providing technical guidance to other data scientists.
• Strong problem-solving, communication, and technical documentation skills.
• Solid experience in life insurance underwriting, automated underwriting, risk selection, or related insurance analytics.
• Experience with cloud-based analytics platforms, model governance, external data evaluation, or third-party model assessment is an asset.
• Familiarity with actuarial concepts, mortality analytics, or an actuarial designation is an asset but not required.

When you join our team

• We'll empower you to learn and grow the career you want.
• We’ll recognize and support you in a flexible environment where well-being and inclusion are more than just words.
• As part of our global team, we'll support you in shaping the future you want to see.

About Manulife and John Hancock

Manulife Financial Corporation is a leading international financial services provider, helping people make their decisions easier and lives better. To learn more about us, visit https://www.manulife.com/en/about/our-story.html .

Manulife is an Equal Opportunity Employer

At Manulife/John Hancock, we embrace our diversity. We strive to attract, develop and retain a workforce that is as diverse as the customers we serve and to foster an inclusive work environment that embraces the strength of cultures and individuals. We are committed to fair recruitment, retention, advancement and compensation, and we administer all of our practices and programs without discrimination on the basis of race, ancestry, place of origin, colour, ethnic origin, citizenship, religion or religious beliefs, creed, sex (including pregnancy and pregnancy-related conditions), sexual orientation, genetic characteristics, veteran status, gender identity, gender expression, age, marital status, family status, disability, or any other ground protected by applicable law.

It is our priority to remove barriers to provide equal ac

The role being advertised is an existing vacancy.