Senior Data Scientist, Strategic Analytics
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 engineering colleagues on analytical data requirements, feature construction, and data quality improvements.
- Review and challenge the suitability of external data sources, including limitations, biases, and operational considerations.
- Stakeholder Engagement:
- Partner with internal teams (Pricing, Underwriting, 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.
- Governance & Reporting:
- 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, including Data Insight Steering Committee (DISC), Protection Market Leadership Committee’s, and R&D Leadership.
Qualifications & Experience
- Experience:
- Significant experience (5–8+ years) in data science/advanced analytics roles, with 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.
- Technical Skills:
- Strong 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.
- Familiarity with model validation, performance monitoring, and explainability approaches.
- Domain Knowledge:
- 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.
- Soft Skills:
- Strong 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.
Benefits
- Leave
- 25 days of annual leave with option to buy/sell more days
- Adoption and fertility leave
- Generous enhanced parental leave
- Healthcare
- Comprehensive private insurance coverage for employee and dependents
- Group Life Insurance coverage of 9x basic annual salary and Group Income Protection up to 75% of basic annual salary
- Optical benefits
- Savings & Retirement
- 15% combined employee/employer contributions
- Wellness
- Subsidised gym membership
- Access to Employee Assistance Program
- Cycle to Work and Electric Car Salary Sacrifice Scheme
- Time off for volunteering
- Charitable matching of employee donations
We are committed to a culture of diversity and inclusion that embraces the authenticity of all employees, partners and communities. We support all employees to thrive and achieve their fullest potential.
As part of our commitment to diversity and inclusion, we will provide reasonable adjustments during the recruitment process to ensure equal access to applicants with disabilities. Please contact us about your needs so that we can discuss these with you to make sure that suitable adjustments are made, where possible.
#J-18808-Ljbffr”, “datePosted”: “2026-05-20”, “hiringOrganization”: { “@type”: “Organization”, “name”: “Pacific Life Re”, “sameAs”: “https://uk.whatjobs.com/pub_api__cpl__436827962__4861?utm_campaign=publisher&utm_medium=api&utm_source=4861&geoID=299” }, “jobLocation”: { “@type”: “Place”, “address”: { “@type”: “PostalAddress”, “addressLocality”: “London” } } }Senior Data Scientist, Strategic Analytics
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 engineering colleagues on analytical data requirements, feature construction, and data quality improvements.
- Review and challenge the suitability of external data sources, including limitations, biases, and operational considerations.
- Stakeholder Engagement:
- Partner with internal teams (Pricing, Underwriting, 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.
- Governance & Reporting:
- 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, including Data Insight Steering Committee (DISC), Protection Market Leadership Committee’s, and R&D Leadership.
Qualifications & Experience
- Experience:
- Significant experience (5–8+ years) in data science/advanced analytics roles, with 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.
- Technical Skills:
- Strong 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.
- Familiarity with model validation, performance monitoring, and explainability approaches.
- Domain Knowledge:
- 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.
- Soft Skills:
- Strong 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.
Benefits
- Leave
- 25 days of annual leave with option to buy/sell more days
- Adoption and fertility leave
- Generous enhanced parental leave
- Healthcare
- Comprehensive private insurance coverage for employee and dependents
- Group Life Insurance coverage of 9x basic annual salary and Group Income Protection up to 75% of basic annual salary
- Optical benefits
- Savings & Retirement
- 15% combined employee/employer contributions
- Wellness
- Subsidised gym membership
- Access to Employee Assistance Program
- Cycle to Work and Electric Car Salary Sacrifice Scheme
- Time off for volunteering
- Charitable matching of employee donations
We are committed to a culture of diversity and inclusion that embraces the authenticity of all employees, partners and communities. We support all employees to thrive and achieve their fullest potential.
As part of our commitment to diversity and inclusion, we will provide reasonable adjustments during the recruitment process to ensure equal access to applicants with disabilities. Please contact us about your needs so that we can discuss these with you to make sure that suitable adjustments are made, where possible.
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