About The Job You're Considering

Successful execution of Digital Lean requires helping lead a fundamental shift in how technology services are delivered. This role sits at the forefront of that change—driving a move toward an AI‑driven, product‑first mindset that uses data to anticipate issues, empower end users, and resolve problems before they escalate. As a full‑stack data scientist, you will turn complex operational signals into insight—and translate that insight into lightweight products, prototypes, and tools that reshape service delivery at scale.

Positioned at the intersection of data science, GenAI, and product thinking, you will work directly with product and delivery teams to surface non‑obvious opportunities, establish a clear point of view, and help convert ideas into durable, intelligent solutions that continuously improve how work gets done.

This is not a pure research role and not a traditional software engineering role. We are looking for a builder‑minded data scientist who uses modern AI tools to create, edit, and evolve code; rapidly prototype workflows and products; and partner closely with engineers, subject‑matter experts, and operators to move from insight to sustained impactYou can bring your whole self to work. At Capgemini building an inclusive future is part of everyday life and will be part of your working reality. We have built a representative and welcoming environment, for everyone.

Hybrid working: The places that you work from day to day will vary according to your role, your needs, and those of the business; it will be a blend of Company offices, client sites, and your home; noting that you will be unable to work at home 100% of the time.

Your Role

As a full‑stack, product‑embedded data scientist, you will:

• Transform raw operational data into insight-ready datasets, working across structured and unstructured sources (process data, logs, documents, tickets, free text).
• Interrogate process and operational data to surface inefficiencies, patterns of waste, bottlenecks, rework, and systemic failure modes that are not obvious at first glance.
• Find the nuggets that scale—novel, repeatable insights that go beyond one-off analysis and can be generalized across teams, accounts, or platforms.
• Conduct deep-dive analyses using statistical methods, machine learning, and modern GenAI techniques to uncover root causes, anomalies, and opportunity spaces.
• Leverage GenAI as a force multiplier to explore data, generate hypotheses, create and edit code, accelerate prototyping, and rapidly iterate on analytical approaches.
• Embed with product and delivery teams to help turn insights into prototype tools, workflows, dashboards, or decision aids that can evolve into durable products.
• Translate analytical insight into a clear narrative—connecting data to business impact, operational outcomes, and a compelling vision for scale.
• Influence without authority by helping others see what you see: clearly communicating findings, framing the problem, and aligning stakeholders around action.
• Participate in continuous improvement activities (e.g., goal deployment, Kaizen-style initiatives) to identify where data and tooling can accelerate learning and results.
• Quantify impact by tying insights to measurable outcomes such as efficiency gains, cost reduction, cycle time improvement, or quality uplift.
• Document patterns, methods, and learnings to enable reuse and establish best practices across the broader data science and analytics community.

Your Skills And Experience

• Proven experience in data science, analytics, or applied machine learning, ideally in operational, process, or product‑adjacent environments.
• Bachelor’s, Master’s, or Ph.D. in a quantitative or computational field (e.g., Computer Science, Statistics, Applied Mathematics, Operations Research, Engineering, or similar).
• Strong hands-on capability with data science tools (e.g., Python, SQL, notebooks, visualization tools) and comfort working end‑to‑end from raw data to insight.
• Deep analytical instincts—you are driven to ask better questions, challenge assumptions, and uncover non‑obvious relationships in data.
• Comfort with GenAI tools and techniques, using them to explore, prototype, and accelerate analysis and lightweight development (not as a black box, but as a collaborator).
• Ability to create and modify code with the help of AI, even if you are not a full-time software engineer.
• Strong grounding in statistics, machine learning, and model interpretation, with good judgment about when each is appropriate.
• Exceptional communication skills—able to clearly articulate insights, tell a compelling story with data, and help others internalize and act on your point of view.
• Demonstrated track record of delivering measurable business or operational impact through data‑driven work.
• Experience with process analytics, operational telemetry, or large‑scale enterprise data.
• Exposure to product analytics, internal tool-building, or analytics‑driven product development.

We are a Disability Confident Employer

Capgemini is proud to be a Disability Confident Employer (Level 2) under the UK Government’s Disability Confident scheme.
As part of our commitment to inclusive recruitment, we will offer an interview to all candidates who:

Please opt in during the application process.

Your security clearance and pre-employment checks

To be successfully appointed to this role, it is a requirement to obtain Security Check (SC) clearance

To obtain SC clearance, the successful applicant must have resided continuously within the United Kingdom for the last 5 years, along with other criteria and requirements.

Throughout the recruitment process, you will be asked questions about your security clearance eligibility such as, but not limited to, country of residence and nationality.

Some posts are restricted to sole UK Nationals for security reasons; therefore, you may be asked about your citizenship in the application process.

If you are successfully offered this position, you will go through a series of pre-employment checks, including: identity, nationality (single or dual) or immigration status, employment history going back 3 continuous years, and unspent criminal record check (known as Disclosure and Barring Service)

Make it real – what does it mean for you?

Why you should consider Capgemini

Growing clients’ businesses while building a more sustainable, more inclusive future is a tough ask. But when you join Capgemini, you join a thriving company and become part of a diverse collective of free-thinkers, entrepreneurs and industry experts. A powerful source of energy that drives us all to find new ways technology can help us reimagine what’s possible. It’s why, together, we seek out opportunities that will transform the world’s leading businesses. And it’s how you’ll gain the experiences and connections you need to shape your future. By learning from each other every day, sharing knowledge and always pushing yourself to do better, you’ll build the skills you want. And you’ll use them to help our clients leverage technology to grow their business and give innovation that human touch the world needs. So, it might not always be easy, but making the world a better place rarely is.

About Capgemini

Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organisations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of over 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2025 global revenues of €22.5 billion.

Get the Future You Want | www.capgemini.com