Lead Data Scientist

SR2 | Socially Responsible Recruitment | Certified B Corporation
London
3 weeks ago
Create job alert
Overview

SR2 | Socially Responsible Recruitment | Certified B Corporation pay range: Up to £115k + equity. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

The Role

Principal AI Recruiter | Founder of The AI Collective

Role focus: Build and scale a brand-new data science function within an established AI company. The function will work exclusively on financial services projects, so prior FS experience is required. This role combines hands-on technical work with leadership, strategy, and client-facing impact. You\'ll work directly with senior decision-makers in banking, fintech, and insurtech, while mentoring and developing a high-calibre data science team.

Key responsibilities:

  • Establish and grow a dedicated data science function focused on financial services use cases.
  • Set technical direction, define best practices, and shape the roadmap for client delivery.
  • Lead projects end-to-end from discovery and experimentation to POC and large-scale deployment.
  • Deliver advanced solutions across ML and AI, including agentic systems and LLM-powered applications.
  • Act as a senior point of contact for FS stakeholders, influencing both technical and commercial outcomes.
  • Hire, mentor, and develop a team of data scientists to a best-in-class standard.
What We’re Looking For
  • Strong background in machine learning, statistical modelling, and applied data science.
  • Expert in Python and familiar with standard ML/AI frameworks (e.g. Scikit-Learn, PyTorch, TensorFlow).
  • Solid track record of delivering successful projects within FS – ideally in regulated, enterprise-grade environments.
  • Previous leadership experience and ability to guide strategy, make architectural decisions, and manage technical teams.
  • Excellent comms and stakeholder management skills, comfortable in senior client-facing settings.
  • Bonus points for consulting experience.
Why Join?
  • Shape and lead a new capability from day one.
  • Work on complex, high-impact problems at the frontier of financial services and AI.
  • Combine technical leadership with direct client influence.
  • Join a company where innovation, collaboration, and professional growth are at the heart of how they operate.

If you’re motivated by the idea of building something new, leading a team, and driving AI adoption.

Seniority level
  • Mid-Senior level
Employment type
  • Full-time
Job function
  • Finance and Information Technology
Industries
  • IT Services and IT Consulting
  • Software Development
  • Financial Services


#J-18808-Ljbffr

Related Jobs

View all jobs

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist - Deep Learning Practitioner

Lead Data Scientist - Deep Learning Practitioner

Lead Data Scientist - Deep Learning Practitioner

Lead Data Scientist - Deep Learning Practitioner

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.