Data Science Consultant

Capgemini Invent
Manchester
2 months ago
Applications closed

Related Jobs

View all jobs

Data Science Consultant – Capital Markets

Data Science Consultant - Health

Data Science Consultant - Gen-AI

Data Science Consultant

Data Science Consultant

Data Science Consultant

Overview

Data Science Consultant role at Capgemini Invent. Capgemini Invent is a transformation consultancy that blends strategic, creative and scientific capabilities. We aim to deliver cutting‑edge solutions through data science, AI and analytics to help clients tackle today's challenges.


Your Role

  • Supporting the delivery of AI, Data Science and Analytics projects, ensuring client expectations are met at all stages.
  • Inspiring clients on exploiting Gen AI, data science and analytics through demonstrations.
  • Developing and deploying new skills in AI, Data Science and Analytics, using current methods where appropriate.
  • Delivering work in a structured manner, balancing creativity and practicality to meet client standards efficiently within agreed timescales.
  • Working effectively in a team, supporting peers to deliver at pace and meet our high internal standards of output and delivery.
  • Contributing to business and personal growth through activities in the following categories: Business Development, Internal Contribution, Learning & Development.

Business Development

  • Contributing to proposals, RFPs, bids, proposition development, client pitch contribution, client hosting at events.

Internal Contribution

  • Campaign development, internal think‑tanks, whitepapers, practice development (operations, recruitment, team events & activities), offering development.

Learning & Development

  • Training to support your career development and the skill demand within the company, certifications etc.

Profile

We’d Love To Meet Someone With



  • Experience in AI, Data Science and Analytics, proven track record across the ML lifecycle, strong foundation in statistical modelling, natural language processing, time‑series analysis, spatial analysis, and mathematical modelling.
  • Keen to demonstrate the potential of Gen AI to unlock business value.
  • A desire to provide solutions to real‑world data challenges, strong stakeholder management and presentation skills, enabling clients to derive better value and insights.
  • Currently working in a major consulting firm or industry with a consulting background, proven ability to succeed in a matrixed organisation and to enlist support for consulting solutions.
  • Architectural and feature knowledge of Google Cloud Platform, AWS, Azure, Databricks; proficiency in Python, R, Pyspark, Scala, PowerBI, Tableau.

What You’ll Love About Working Here

Data Science Consulting brings an inventive quantitative approach to our clients’ biggest business and data challenges, unlocking tangible value through intelligent products and solutions. We focus on exploring AI possibilities, accelerating impact with proof of value, and scaling AI responsibly.


Need To Know

We are committed to inclusion and offer a positive work‑life balance, hybrid working, flexible arrangements, wellbeing support, and community impact initiatives.


About Capgemini Invent

Capgemini Invent is a global business and technology transformation partner, driving digital and sustainable transformation for enterprises worldwide.


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

Careers

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

Jobs

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

Education

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.

🍪 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.