Pacific Life Re
insurance or reinsurance
SeniorDataScientist,StrategicAnalytics
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Data Scientist, Strategic Analytics at Pacific Life Re. Skills: advanced analytics, data science techniques, predictive models, analytical approaches, risk assessment, underwriting innovation, pricing-adjacent use cases, data analysis, model development. Design, build, and deploy advanced analytical models using large, complex datasets. Apply statistical, machine learning, and data science techniques to generate insight across risk assessment, underwriting innovation, and pricing-adjacent”
Industry & Context.
applying advanced analytics, data science techniques, and emerging data sources to deepen understanding of insurance risk; deepen understanding of insurance risk; support commercial decision-making; developing and interpreting predictive models and analytical approaches; generate insight across risk assessment, underwriting innovation, and pricing-adjacent use cases; assessing predictive value, bias, stability, and practical applicability; translate analytical outputs into insights; analytical sophistication with business applicability
What They're Looking For.
Must Have
Significant experience (5–8+ years) in data science/advanced analytics roles, Demonstrable experience in insurance or reinsurance environments, Proven track record of developing predictive models and analytical solutions that have informed underwriting, pricing, or risk decisions, Experience working in multi-disciplinary teams alongside actuaries, underwriters, and commercial stakeholders, Hands-on capability in Python for data analysis and model development, Confident querying and working with large structured datasets using SQL, Experience with statistical modelling, machine learning techniques, and feature engineering, Good understanding of insurance or reinsurance products, underwriting processes, and risk selection concepts, Experience working with sensitive data (e. g. medical or personal data) and an appreciation of regulatory and ethical considerations, Communication skills, with the ability to explain complex analytical concepts to non-technical audiences, Comfortable operating as a senior individual contributor, influencing through expertise rather than authority, Pragmatic mindset, balancing analytical sophistication with business applicability
Nice to Have
Experience with model validation, performance monitoring, and explainability approaches
What You'll Do.
and deploy advanced analytical models using large
and data science techniques to generate insight across risk assessment
underwriting innovation
and pricing-adjacent use cases
Lead exploratory analysis of new and emerging datasets
assessing predictive value
and practical applicability
Partner closely with actuaries
and underwriters to translate analytical outputs into insights that can be embedded into decision frameworks and business processes
Ensure models and analyses are explainable and appropriately documented for use in commercial
and governance contexts
Contribute to the evolution of analytics standards
and reusable approaches within Strategic Analytics
Leverage the Strategic Analytics Data Analytics Platform (DAP) and self service analytics tooling to develop scalable
reproducible analyses
Collaborate with data engineering colleagues on analytical data requirements
and data quality improvements
Review and challenge the suitability of external data sources
including limitations
and operational considerations
Partner with internal teams (Pricing
and Client Solutions) and external clients on predictive modelling and innovative data utilisation
Support selected client-facing initiatives and discussions where advanced analytics expertise is required
Represent the organisation at industry forums and contribute to thought leadership
Support selected client facing initiatives and discussions where advanced analytics expertise is required
Contribute to internal thought leadership on the application of data science within insurance and reinsurance
How You'll Work.
Team & Collaboration
working closely with actuarial, pricing, underwriting, and client teams; Partner closely with actuaries, pricing teams, and underwriters; Collaborate with data engineering colleagues; Partner with internal teams (Pricing, Underwriting, and Client Solutions) and external clients; Experience working in multi-disciplinary teams alongside actuaries, underwriters, and commercial stakeholders
Communication Scope
communication skills, with the ability to explain complex analytical concepts to non-technical audiences
Process & Methodology
leadership of discrete analytics initiatives, leading defined workstreams or projects
Full Job Description
**Job Title** Senior Data Scientist, Strategic Analytics ****Job Description**** **Role Purpose** The Senior Data Scientist, Strategic Analytics is a senior analytics professional who combines hands‑on technical contribution with leadership of discrete analytics initiatives. The role is responsible for applying advanced analytics, data science techniques, and emerging data sources to deepen understanding of insurance risk and support commercial decision‑making. Operating within the Strategic Analytics team, the role involves both personally developing and interpreting predictive models and analytical approaches, and leading defined workstreams or projects—working closely with actuarial, pricing, underwriting, and client teams to ensure insights are robust, explainable, and decision‑relevant. **Key Responsibilities** * **Research & Analytics Initiatives:** * Design, build, and deploy advanced analytical models using large, complex datasets, including underwriting, medical, behavioural, and external third‑party data. * Apply statistical, machine learning, and data science techniques to generate insight across risk assessment, underwriting innovation, and pricing‑adjacent use cases. * Lead exploratory analysis of new and emerging datasets, assessing predictive value, bias, stability, and practical applicability. * **Strategic Analytics Integration:** * Partner closely with actuaries, pricing teams, and underwriters to translate analytical outputs into insights that can be embedded into decision frameworks and business processes. * Ensure models and analyses are explainable and appropriately documented for use in commercial, client, and governance contexts. * Contribute to the evolution of analytics standards, best practices, and reusable approaches within Strategic Analytics * **Data & Technology:** * Leverage the Strategic Analytics Data Analytics Platform (DAP) and self service analytics tooling to develop scalable, reproducible analyses. * Collaborate with data engi
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