Lead Data Scientist

About The Job You're Considering

Successful execution of Digital Lean requires helping lead afundamental shift in how technology services are delivered. This role sits at the forefront of that change driving a move toward anAIdriven, product first mindsetthat uses data to anticipate issues, empower end users, and resolve problems before they escalate. As a fullstack 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 nonobvious 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 impact

You 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 fullstack, 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 teamsto 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 impactby tying insights to measurable outcomes such as efficiency gains, cost reduction, cycle time improvement, or quality uplift.
• Document patterns, methods, and learningsto 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.
• Bachelors, Masters, 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 endtoend from raw data to insight.
• Deep analytical instincts you are driven to ask better questions, challenge assumptions, and uncover…