Senior Data Scientist (PA)

Munich Re
London
3 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

Senior Data Scientist

SENIOR DATA SCIENTIST - Computer Vision / Generative AI HYBRID

Senior Data Scientist – Machine Learning -  Defence –Eligible for SC

Senior Data Scientist

Senior Data Scientist

About UK Life Branch:

With the office in London, it forms the Life 1 division of Munich Re. The UK life market is one of the, if not the, most competitive life markets in the world. We understand that Life insurers work in a dynamic market where medical progress, demographic trends and changing lifestyles are constantly giving rise to new risk landscapes. This demanding situation is made even more challenging by changing laws and regulations and ever tougher competition. So we need a smart strategy and structure in order to succeed.

At UK & Ireland Life we have three pillars to our business strategy, protection, longevity and reinsurance structuring. All three are key to the success of our business so it's important to look at the big picture.
In terms of clients, we trust them as experts of their business and provide them with the financial strength of the world's largest reinsurer, global expertise and sharp pricing so that they are both competitive and profitable.

About the role:

The role holder is responsible for taking a leading role in the delivery of UKLB's Predictive Analytics initiative to support growth across all its lines of business by harnessing data-model-driven insights to meet our ambitions.

Key Responsibilities:

  1. Deliver the Predictive Analytics roadmap to achieve data-model driven stakeholder value for UKLB and our clients. Assist the Head of Predictive Analytics in establishing and developing a mature Data & Analytics culture and its talent to deliver data-model-driven stakeholder value.
  2. Provision of advanced pensioner demographics and mortality basis based on optimal exploitation of newly acquired data sets, enabling a build-up of a competitive Flow proposition, and enhancing accuracy and efficiency to expand the overall Longevity business portfolio.
  3. Identify potential solutions to support the Protection line of business on new propositions across underwriting, claims and distribution where Predictive Analytics can deliver new insights and solutions to reduce friction.
  4. Conceptualize and offer analytics products and services to internal and external stakeholders along the whole value chain by using modern statistical methods like GLM, machine learning and where applicable, Knowledge Graphs and Large Language Models.
  5. Development of culture, policies (including review) and strategy relating to predictive analytics for pricing and ToT (terms of trade) review.
  6. Collaborate with cross-functional and regional teams to promote data-driven decision-making culture, and provide training and support to employees on data analytics best practices.
  7. Maintain knowledge on emerging GenAI and data scientist practices and share within the team.
  8. Establish and maintain robust data and analytics governance frameworks, policies, and procedures to ensure quality, security, and compliance with industry regulations.
  9. Deputise for the Head of Predictive Analytics as and when required.
  10. Direct line management when required of Data Scientists.
  11. Develop strong client-focused relationships with the other Pricing teams as well as the commercial Longevity and Protection teams. Construct an important branch wide network of contacts.
  12. Input in to team discussions to help set the direction of the team, inputting in to non-technical topics (including people and culture).

Competencies:

Strategic mindset (we think big) -you look, plan and move into the future with clear intentions and purposeful actions, seeking regular feedback, that allows you to make decisions today that will lead the business towards its future commitments.

Ensures accountability (we lead the 'we')- you hold yourself and others accountable to take responsibility and meet commitments, creating a culture where people own their decisions and actions and appreciate how they contribute to the team/organisation commitments.

Managing complexity (we grow with our clients)- you make sense of complex and sometimes contradictory information to effectively solve problems, learning and sharing along the way.

Sponsors work (we care and dare)- you know when to lead and when to let others lead, providing direction and delegating to others, empowering and trusting them to achieve their commitments.
Develops talent (we care and dare)- you develop the team to meet their career ambitions, building capability at an individual and organisational level, preparing them for future opportunities. You discuss feedback and development regularly and promote a diverse and inclusive workforce.

Being resilient (we are clear and authentic) -setbacks are unavoidable; however, you recover quickly, seek feedback, learn and unlearn and move forward with courage and commitment.

Key Skills & Experience:

  1. Several years of experience in key aspects of data analytics within Life and Health reinsurance, including actuarial concepts, risk assessment, and pricing methodologies.
  2. Deep expertise in data manipulation, statistical analysis, and predictive modelling using tools such as R, Python, SAS, or similar, in a life insurance environment.
  3. Experience with the following is a plus: Azure components, Databricks, graph analytics, GenAI, Large Language Models, Knowledge Graphs.
  4. Experience with data visualization tools, such as Tableau or Power BI, to communicate analytical insights.
  5. Excellent communication and presentation skills; consulting or project management experience is a plus. Ability to communicate technical concepts to different audiences.
  6. Familiarity with data privacy and AI regulatory frameworks in the (re)insurance industry.
  1. In-depth knowledge of state-of-the-art machine learning algorithms.
  2. Highly motivated, proactive and innovative mindset, with a passion for leveraging data and analytics to drive business value.
  3. Confidence and diplomacy to challenge peers and manage upwards.
  4. Ability to build an understanding of internal and external client strategy and needs.

Qualifications and Educational Requirements:

  1. Degree, Master's degree or Ph.D. in a relevant field such as Computer Science, Statistics, Economics or Applied Mathematics.

People Leader:

You are aware of your role (as a leader) in being able to influence your team structure and culture to promote principles of diversity and inclusion.

You strive to continuously educate yourself on best practice for inclusive leadership.

You demonstrate and role model inclusive behaviour and encourage your colleagues to play an active role in creating an inclusive culture as well.

You support a culture in which high ethical conduct is recognised, valued and embodied by all.

You treat everyone fairly and with respect.

Benefits:

You will be rewarded with a great compensation package, on target bonus, 25 days annual leave with the option to purchase more along with private medical insurance and employers' contributory pension of 10%.

We are one of the few employers to offer fully paid 6 months family leave for times when you need it the most.

Diversity, Equity & Inclusion

At Munich Re, embracing the power of differences is at the core of who we are. We believe diversity fosters resilience and innovation and enables us to act on our purpose of helping humankind act braver and better. We recognise diversity can be multi-dimensional, intersectional, and complex, so we want to build a diverse workforce that includes a wide range of racial, ethnic, sexual, and gender identities; economic and geographic backgrounds; physical abilities; ages; life, school, and career experiences; and political, religious, and personal beliefs. Additionally, we are committed to building an equitable and inclusive work environment where this diversity is celebrated, valued, and has equitable opportunities to succeed.

If you are excited about this role but your experience does not align perfectly with everything outlined, or you don't meet every requirement, we encourage you to apply anyway. You might just be the candidate we are looking for!

All candidates in consideration for any role can request a reasonable adjustment at any point in our recruitment process. You can request an adjustment by speaking to your Talent Acquisition contact.#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Contract vs Permanent Data Science Jobs: Which Pays Better in 2025?

Data science sits at the intersection of statistics, machine learning, and domain expertise, driving crucial business decisions in almost every sector. As UK organisations leverage AI for predictive analytics, customer insights, and automation, data scientists have become some of the most in-demand professionals in the tech job market. By 2025, data scientists with expertise in deep learning, natural language processing (NLP), and MLOps are commanding top-tier compensation packages. However, deciding whether to become a day‑rate contractor, a fixed-term contract (FTC) employee, or a permanent member of an organisation can be challenging. Each path offers a unique blend of earning potential, career progression, and work–life balance. This guide will walk you through the UK data science job market in 2025, examine the differences between these three employment models, present sample take‑home pay scenarios, and offer strategic considerations to help you determine the best fit for your career.

Data Science Jobs for Non‑Technical Professionals: Where Do You Fit In?

Beyond Jupyter Notebooks Ask most people what a data‑science career looks like and they’ll picture Python wizards optimising XGBoost hyper‑parameters. The truth? Britain’s data‑driven firms need storytellers, strategists, ethicists and project leaders every bit as much as they need statisticians. The Open Data Institute’s UK Data Skills Gap 2024 places demand for non‑technical data talent at 42 % of all data‑science vacancies—roles focused on turning model outputs into business value and trustworthy decisions. This guide highlights the fastest‑growing non‑coding roles, the transferable skills many professionals already have, and a 90‑day action plan to land a data‑science job—no pandas required.

McKinsey & Company Data‑Science Jobs in 2025: Your Complete UK Guide to Turning Data into Impact

When CEOs need to unlock billion‑pound efficiencies or launch AI‑first products, they often call McKinsey & Company. What many graduates don’t realise is that behind every famous strategy deck sits a global network of data scientists, engineers and AI practitioners—unified under QuantumBlack, AI by McKinsey. From optimising Formula One pit stops to reducing NHS wait times, McKinsey’s analytics teams turn messy data into operational gold. With the launch of the McKinsey AI Studio in late 2024 and sustained demand for GenAI strategy, the firm is growing its UK analytics headcount faster than ever. The McKinsey careers portal lists 350+ open analytics roles worldwide, over 120 in the UK, spanning data science, machine‑learning engineering, data engineering, product management and AI consulting. Whether you love Python notebooks, Airflow DAGs, or white‑boarding an LLM governance roadmap for a FTSE 100 board, this guide details how to land a McKinsey data‑science job in 2025.