Senior Data Scientist, Strategic Analytics

Senior Data Scientist, Strategic Analytics

Full-Time 60000 - 80000 € / year (est.) No home office possible
Pacific Asset Management, LLC

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, where innovation meets collaboration.
  • Benefits: Enjoy 25 days annual leave, comprehensive healthcare, and wellness initiatives.
  • Other info: Embrace a culture of diversity, inclusion, and community involvement.
  • 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.

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.

Working For Pacific Life Re

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)

  • 25 days of annual leave with option to buy/sell more days
  • Adoption and fertility leave
  • Generous enhanced parental leave
  • 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
  • 15% combined employee/employer contributions
  • 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

You Can Be Who You Are

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.

Senior Data Scientist, Strategic Analytics employer: Pacific Asset Management, LLC

At Pacific Life Re, we pride ourselves on being an exceptional employer, offering a vibrant work culture that values individual contributions and fosters professional growth. Our London office provides a supportive environment with a strong emphasis on work-life balance, comprehensive benefits, and opportunities for community involvement, making it an ideal place for talented data scientists to thrive and make a meaningful impact in the insurance industry.

Pacific Asset Management, LLC

Contact Detail:

Pacific Asset Management, LLC Recruiting Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Data Scientist, Strategic Analytics

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! Prepare a portfolio of your best data science projects and be ready to discuss them in detail. This will not only demonstrate your expertise but also give you a chance to showcase your problem-solving abilities.

Tip Number 3

Practice makes perfect! Get comfortable with common interview questions for data scientists, especially those related to predictive modelling and analytics. Mock interviews with friends or mentors can help you nail your responses.

Tip Number 4

Apply through our website! We love seeing applications directly from candidates who are genuinely interested in joining us. Plus, it shows you're proactive and keen on being part of our team!

We think you need these skills to ace Senior Data Scientist, Strategic Analytics

Python
SQL
Statistical Modelling
Machine Learning Techniques
Feature Engineering
Predictive Modelling
Data Analysis

Some tips for your application 🫡

Tailor Your CV:Make sure your CV is tailored to the Senior Data Scientist role. Highlight your experience in data science and analytics, especially in insurance or reinsurance. We want to see how your skills align with our needs!

Showcase Your Projects:Include specific examples of predictive models or analytical solutions you've developed. We love seeing real-world applications of your work, so don’t hold back on the details that show your impact!

Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about this role and how your background makes you a perfect fit for our team. We want to feel your enthusiasm!

Apply Through Our Website:Don’t forget to apply through our website! It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining StudySmarter!

How to prepare for a job interview at Pacific Asset Management, LLC

Know Your Data Science Stuff

Make sure you brush up on your Python and SQL skills before the interview. Be ready to discuss specific projects where you've developed predictive models or used machine learning techniques, especially in insurance or reinsurance contexts.

Understand the Business

Familiarise yourself with the insurance industry, particularly underwriting processes and risk assessment. This will help you translate your technical knowledge into business insights during the interview.

Communicate Clearly

Practice explaining complex analytical concepts in simple terms. You might be asked to present your findings to non-technical stakeholders, so being able to communicate effectively is key.

Show Your Leadership Skills

Be prepared to discuss how you've led analytics initiatives or collaborated with cross-functional teams. Highlight your ability to influence decisions through expertise rather than authority, as this is crucial for a senior role.