Data Analyst / Business Analyst – Risk Rating & Pricing

Capgemini
London
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Pricing Analyst (Risk)

Senior Pricing Analyst

Data Analyst (Payments, Risk/ Controls)

Data Analyst (Payments, Risk/ Controls)

Business Data Analyst

Business Data Analyst BELFAST £600/day Banking

Job Title:Data Analyst / Business Analyst – Risk Rating & Pricing


Get The Future You Want!

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.


We are looking to recruitData Analyst /Business Analystto join Capgemini Financial Services. This is a permanent, fulltime position and this represents a unique opportunity for someone to enhance their career


Your Role


  • Work closely with business stakeholders to gather and document requirements related to Risk Rating and Pricing data, tools, and processes.
  • Perform analysis on complex datasets to support pricing model development, calibration, and monitoring.
  • Assist in the identification, mapping, and analysis of relevant data sources and flows across systems.
  • Support the development of data dictionaries, data flow diagrams, and documentation to improve data understanding and usage across the business.
  • Facilitate and document workshops with Underwriting, Actuarial, and Technology teams to gather business input and define technical needs.
  • Collaborate with data engineers to support data acquisition, preparation, and quality assurance processes.
  • Create reports and visualizations (e.g., in Power BI) to communicate insights and support decision-making.
  • Contribute to the testing and validation of pricing tools, ensuring that business and data requirements are met.
  • Act as a liaison between the Underwriting business and the Technology team, translating business needs into deliverable outcomes.
  • Assist in data governance efforts by supporting data quality initiatives and documentation standards.


Experience Required


  • Bachelor’s degree in Computer Science, Information Systems, Data Science, or a related field.
  • Must have knowledge of London Market and Pricing tool ( Radar, HX, Verisk Rulebook)
  • Knowledge of risk rating, pricing models, or actuarial processes is desirable.
  • Proven experience as a Data Analyst/Business Analyst, or in a similar role.
  • Proven ability to document business requirements, data definitions, and system processes clearly and concisely. Additionally knowledge and hands-on experience on tools (e.g., Oracle SQL Developer, Microsoft Visio).
  • Experience with database management systems (e.g., SQL Server, Oracle, MySQL, PostgreSQL).
  • Familiarity with data warehousing concepts and technologies (e.g., ETL processes, OLAP).
  • Proficient in SQL, Excel, and data visualization tools (e.g., Power BI).
  • Understanding of data governance, data quality, and data management best practices.
  • Proficiency in SQL and ability to write complex queries for data extraction and analysis.
  • Excellent communication and collaboration skills.
  • Attention to detail and problem-solving abilities.


For immediate consideration, please can you send me your CV ASAP


About Capgemini

Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world while creating tangible impact for enterprises and society. It is a responsible and diverse group of 350,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market-leading capabilities in AI, cloud, and data, combined with its deep industry expertise and partner ecosystem. The Group reported 2023 global revenues of €22.5 billion.


Get The Future You Want |www.capgemini.com

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.

Jobs Careers

Veterans in Machine Learning: A Military‑to‑Civilian Pathway into AI Careers

Introduction Artificial intelligence is no longer relegated to sci‑fi films—it underpins battlefield decision‑support, fraud detection, and even supermarket logistics. The UK Government’s 2025 AI Sector Deal forecasts an additional £200 billion in GDP by 2030, with machine‑learning (ML) engineers cited as the nation’s second most in‑demand tech role (Tech Nation 2024). The Ministry of Defence’s Defence AI Strategy echoes that urgency, earmarking £1.6 billion for FY 2025–28 to embed ML into planning, logistics, and autonomous systems. If you have ever tuned a radar filter, plotted artillery trajectories, or sifted sensor data for actionable intel, you have already worked with statistical modelling—the backbone of machine learning. This guide shows UK veterans how to reframe military experience for ML roles, leverage MoD transition funding, and land high‑impact positions building the models shaping tomorrow’s defence and commercial landscapes. Quick Win: Bookmark our live board for Machine‑Learning Engineer roles to see who’s hiring today.

Jobs

Rural-Remote Machine Learning Jobs: Finding Balance Beyond the Big Cities

Over the past decade, machine learning (ML) has transformed from a niche research domain into a pervasive technology underpinning everything from recommendation systems and voice assistants to financial forecasting and autonomous vehicles. Historically, the UK’s major tech hubs—particularly London—have been magnets for top ML talent and corporate headquarters. However, remote work has become mainstream, and many ML professionals are realising they can excel in their field while living far beyond the city limits. At MachineLearningJobs.co.uk, we’ve observed a growing interest in positions that allow for a rural lifestyle or a coastal environment, often reflected in search terms like “ML remote countryside” or “tech jobs by the sea.” This surge is no coincidence. Flexible work policies, better rural broadband, and the nature of machine learning tasks—much of which can be done through cloud platforms—are bringing new opportunities to those who wish to swap urban hustle for fresh air and scenic views. Whether you’re a data scientist, ML engineer, researcher, or product manager, a rural or seaside move could reinvigorate your work-life balance. In this article, we’ll unpack why rural-remote ML jobs are on the rise, how you can navigate the challenges of leaving the city, and what you need to do to thrive in a machine learning career beyond the M25. If you’ve dreamt of looking up from your laptop to rolling fields or ocean waves, keep reading—your rural ML role might be closer than you think.

Jobs

Quantum-Enhanced Machine Learning—Propelling AI into the Next Frontier

Machine learning (ML) has revolutionised how we interpret data, build predictive models, and create intelligent applications. From recommendation engines and self-driving cars to advanced genomics and natural language processing, ML solutions are integral to nearly every corner of modern life. However, as data complexity and model size continue to skyrocket, the computational demands placed on ML systems grow in tandem—often pushing even high-performance classical computers to their limits. In recent years, quantum computing has emerged as a tantalising solution to these challenges. Unlike traditional digital systems, quantum computers exploit quantum mechanics—superposition and entanglement—to process information in ways that defy conventional logic. As these machines mature, they promise exponential speed-ups for certain tasks, potentially reshaping how we approach AI and data-intensive challenges. What does this mean for machine learning? Enter quantum-enhanced ML, a new frontier where quantum processors and classical ML frameworks unite to accelerate model training, tackle high-dimensional data, and solve complex optimisation tasks more efficiently. In this article, we will: Unpack the current state of machine learning, highlighting key bottlenecks. Provide a concise overview of quantum computing—why it’s radical and how it differs from classical technology. Examine potential breakthroughs in quantum-enhanced ML, including real-world use cases and technical approaches. Explore the roles and skill sets that will define this quantum-AI era, with guidance on how to prepare. Discuss the roadblocks (like hardware maturity and ethical concerns) and how they might be addressed in the years to come. If you’re a machine learning engineer, data scientist, or simply an AI enthusiast fascinated by the next wave of computational innovation, read on—quantum computing could become an integral part of your future toolkit, opening up job opportunities and reimagining what ML can achieve.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.