Data Science Consultant

83zero
London
1 month ago
Applications closed

Related Jobs

View all jobs

Data Science Consultant - Health

Data Science Consultant – Capital Markets

Data Science Consultant - Gen-AI

Data Science Consultant — Hybrid & Impactful

Senior Data Science Consultant - Hybrid Analytics

Health Data Science Consultant — Hybrid Role

Data Science Offering Lead

Salary: £80,000 – £100,000 + benefits

Location: UK-wide (client-site travel required)

Clearance: SC or SC-clearable

Type: Permanent


We’re partnering with a growing consulting business that is expanding its Data & AI practice and looking for a Data Science Offering Lead to shape and build their end-to-end data science and ML capability. This role focuses on designing offerings, leading client engagements and delivering practical, production-ready ML and AI solutions that create measurable value.


What you’ll be doing

  • Leading the development of the firm’s Data Science, ML and AI offering and go-to-market strategy.
  • Working closely with clients to understand business problems and translate them into robust data-driven solutions.
  • Designing and overseeing ML models, AI prototypes, PoCs, MVPs and scalable production solutions.
  • Driving standards, best practices and technical excellence across all data science engagements.
  • Supporting pre-sales, shaping proposals and leading workshops to demonstrate the art of the possible.
  • Collaborating with engineering, strategy and consulting teams to deliver impactful AI-led transformation.
  • Mentoring data scientists and helping build a strong, modern internal capability.
  • Travelling nationally when required to support client delivery.

What you’ll bring

  • Strong experience across data science, machine learning and applied AI.
  • Proven ability to design end-to-end ML solutions—from discovery and modelling through to deployment.
  • Excellent client-facing skills with the confidence to lead senior stakeholder conversations.
  • Consulting experience and the ability to deliver clarity in complex or ambiguous situations.
  • Good understanding of cloud ML platforms and modern tooling (Azure, AWS, GCP, MLflow, etc.).
  • Passion for innovation, experimentation and pushing boundaries in AI/ML delivery.
  • SC clearance or the ability to become SC-cleared.

Interested?

If this sounds like a role you’d thrive in, drop me your details for more information and a confidential conversation.

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.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

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

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.