At a Glance
- Tasks: Lead advanced analytics projects and develop predictive models to drive insurance insights.
- Company: Join a dynamic team at Pacific Life Re, committed to innovation and collaboration.
- Benefits: Enjoy 25 days annual leave, comprehensive healthcare, and wellness initiatives.
- Other info: Embrace a culture of diversity, inclusion, and work-life balance while growing your career.
- Why this job: Make a real impact in the insurance industry with cutting-edge data science techniques.
- Qualifications: 5-8 years in data science, strong Python and SQL skills, and insurance knowledge.
The predicted salary is between 60000 - 80000 € per year.
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.
- 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.
Every person in our global team is valued for the unique qualities they bring to our business and we seek to build their expertise and support their individual ambitions at every step. Of course, we take our work seriously and we know our team can operate under great pressure. We work hard and thrive on achievement, but we also know how to have fun and relax too. We regularly host a range of team building days to strengthen our team's connection with each other and reflect on their successes. Providing employees with a healthy work-life balance is very important to our culture. We have a wide range of employee benefits and we host regular social activities and well-being initiatives. We are also committed to supporting our employee's involvement in their communities, by actively fundraising, hosting charity events and overseeing volunteering opportunities.
Benefits (Only for Permanent and Fixed Term Employees)- 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: Subsidized 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.
Pacific Life Re ValuesPlease click here to view our company values.
Senior Data Scientist, Strategic Analytics in London employer: Pacific Life Re
At Pacific Life Re, we pride ourselves on being an exceptional employer that values the unique contributions of each team member. Our culture promotes a healthy work-life balance, with generous benefits including 25 days of annual leave, comprehensive healthcare coverage, and opportunities for community involvement through volunteering and charity events. We foster a collaborative environment where employees can grow their expertise while enjoying team-building activities and social initiatives, making it a rewarding place to advance your career as a Senior Data Scientist in the heart of the insurance industry.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist, Strategic Analytics in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, especially those who work in analytics or insurance. A friendly chat can lead to insider info about job openings that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your predictive models and analytical projects. This is your chance to demonstrate your hands-on experience and technical prowess in Python and SQL.
✨Tip Number 3
Prepare for interviews by brushing up on your communication skills. You’ll need to explain complex concepts clearly, so practice breaking down your past projects into simple terms that anyone can understand.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Senior Data Scientist, Strategic Analytics in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior Data Scientist role. Highlight your experience with predictive models and analytics in insurance or reinsurance. We want to see how your skills align with our needs!
Showcase Your Technical Skills:Don’t forget to showcase your hands-on experience with Python and SQL. Mention specific projects where you’ve applied machine learning techniques or worked with large datasets. This is your chance to shine!
Craft a Compelling Cover Letter:Your cover letter should tell us why you’re the perfect fit for this role. Share your passion for data science and how you can contribute to our Strategic Analytics team. Keep it engaging and personal!
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss any important updates from us!
How to prepare for a job interview at Pacific Life Re
✨Know Your Data Science Stuff
Make sure you brush up on your Python and SQL skills. Be ready to discuss specific projects where you've developed predictive models or used machine learning techniques. They’ll want to see how you can apply these skills in real-world scenarios, especially in insurance or reinsurance contexts.
✨Understand the Business
Familiarise yourself with the insurance industry, particularly underwriting processes and risk assessment. Being able to speak knowledgeably about how your analytical insights can impact decision-making will set you apart from other candidates.
✨Communicate Clearly
Practice explaining complex analytical concepts in simple terms. You’ll likely be working with non-technical stakeholders, so showing that you can bridge the gap between data science and business needs is crucial.
✨Show Your Leadership Skills
Even if you're applying for a senior role, they’ll want to see your ability to lead projects and collaborate with multi-disciplinary teams. Prepare examples of how you've successfully led initiatives or influenced decisions through your expertise.