National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Credit Risk Analyst / Data Scientist

Eden Smith Group
Kent
2 weeks ago
Create job alert

Are you looking to leave your starter jobs and progress your career in Credit Risk & Data Science? Do you want to work in a fast paced environment where you can make an immediate impact?


*PLEASE NOTE* - All Candidates MUST be able to commute ON-SITE to Seven Oaks, Kent 3 days per week. Public Transport is limited so IDEALLY candidate will hold a full UK drivers licence and own car.


We are hiring aCredit Risk Analyst / Data Scientistto join a collaborative and innovative team that is shaping the future of credit risk modelling and forecasting. This is a fantastic opportunity to work closely with experienced professionals and gain hands on experience in predictive modelling, loss forecasting, and machine learning, all within a growing, tech enabled financial services organisation.


The Role

You will be part of a small, high impact data science team responsible for:

  • Developing predictive modelssuch as scorecards and machine learning models for customer acquisitions and collections
  • Supporting loss forecastingfor both new business and the existing portfolio
  • Exploring new data sourcesand modelling techniques to improve performance and accuracy
  • Working with tools like Python, T SQL, and Excelto manage data workflows and build solutions
  • Collaborating across departmentswith teams in credit risk, finance, capital markets, and operations
  • Monitoring model performanceand contributing to regular validation and compliance reporting


What you'll need?

  • A degree, orstrong mathematical ability, in a numerate subject such as Mathematics, Statistics, Data Science, Economics, or Physics
  • 1 to 2 years of experience in aFinancial datadriven environment, or strong academic project experience
  • Familiarity withmodelling techniqueslike logistic regression or basic machine learning
  • A keen interest in data science and its applications in finance or risk
  • Strong attention to detail and a problem solving mindset
  • A confident communicator who can explain data insights to both technical and non technical audiences
  • A willingness to learn. For example, experience inPython/R, AWSor model deployment would be great, but it is important that you could learn this


Why work for us?

  • Work in a high growth, data first business combining fintech agility with financial service rigour
  • Be part of a collaborative and forward thinking team where your input matters
  • Gain exposure to real world business problems and end to end model development
  • Hybrid working available, with regular team interaction and support
  • On site parking and scenic office location in Sevenoaks (a driving licence is helpful due to limited public transport)

Related Jobs

View all jobs

Credit Risk Analyst / Data Scientist

Credit Risk Analyst / Data Scientist

Credit Risk Analyst / Data Scientist

Credit Risk Analyst / Data Scientist

Credit Risk Analyst / Data Scientist

Credit Risk Analyst / Data Scientist

National AI Awards 2025

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 to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.

Machine Learning Jobs UK 2025: 50 Companies Hiring Now

Bookmark this page—we refresh the Hotlist every quarter so you always know who’s really scaling their ML teams. The UK’s National AI Strategy, a £2 billion GenAI accelerator fund and a record flow of private capital have kicked ML hiring into overdrive for 2025. Whether you build production‑grade LLM services or optimise on‑device models for edge hardware, employers need your skills now. Below you’ll find 50 organisations that advertised UK‑based machine‑learning vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the type of employer—and mission—that excites you. For each company we list: Main UK hub Example live or recent vacancy Why it’s worth a look (stack, impact, culture) Search any employer on MachineLearningJobs.co.uk to see real‑time adverts, or set a free alert so fresh openings drop straight in your inbox.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.