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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in statistical modeling, machine learning, and data analysis to drive business insights and decision-making. Proficient in leading data science projects from conception to implementation while mentoring team members and collaborating with cross-functional stakeholders.
Highest-signal resume keywords
Statistical ModelingMachine LearningPython or R ProficiencySQL ProficiencyLife Insurance Underwriting
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data AnalysisPredictive AnalyticsModel EvaluationExperimental DesignAnalytical Solution Development
Soft Skills
Problem-SolvingCommunicationTechnical Documentation
Tools & Technologies
Cloud-Based Analytics PlatformsData Governance Tools
Industry Keywords
Life Insurance AnalyticsAutomated UnderwritingRisk SelectionActuarial ConceptsMortality Analytics
Tech Stack
Tools & technologiesCloudPythonSQL
About the role
Key responsibilities & impact- 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 for business problems
- 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
- Prepare technical documentation for implementation, validation, governance, and ongoing model management
- Provide technical direction, review analytical work, and mentor data scientists and other analytical contributors
- Translate complex business needs into rigorous analytical approaches and communicate recommendations to technical and business stakeholders
Requirements
What you’ll need- 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
- 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
Benefits
Comp & perks- Learning and career growth support
- Flexible work environment
- Well-being and inclusion support
- Health insurance
- Dental insurance
- Mental health benefits
- Vision insurance
- Short- and long-term disability insurance
- Life and AD&D insurance coverage
- Adoption/surrogacy benefits
- Wellness benefits
- Employee/family assistance plans
- Retirement savings plans
- Pension/401(k) savings plans
- Global share ownership plan with employer matching contributions
- Financial education and counseling resources
- Up to 11 paid holidays
- 3 personal days
- 150 hours of vacation
- 40 hours of sick time, or more where required by law
- Statutory leaves of absence
- Incentive programs and incentive compensation tied to business and individual performance