Senior Data Science Consultant - Credit Decisioning

Experian Group
London
8 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Science Consultant: Bayesian Pricing & Marketing Optimization

frog - Senior Consultant - Data Science (Customer Data)

Senior GIS & Data Science Consultant (Hybrid)

Senior Data Scientist & Consultant: Drive Real Impact

Lead GIS & Data Science Consultant (Hybrid)

AI & Data Science Manager / Senior Manager

We have a new vacancy for an experiencedSenior Data Science Consultantwithcoding expertise in Python or SASto join our Analytics team, working with our cloud-based Ascend platform. You will partner with clients to understand their business, identify what data is required and how clients can best use Experian data models and analytics to improve business outcomes.

Responsibilities include:

  • Design analytics solutions to client's problems in any area of consumer lending and credit risk management, using Experian analytics solutions.
  • Engage in a consultative way with the client, to identify problems and define, design and deliver analytics solutions, with expertise in credit risk modelling and optimisation techniques.
  • Present proposals to clients for analytics solutions, including recommendations.
  • Provide consultancy on the potential 'bigger picture' strategies.
  • Co-ordinate with Experian's Analytics Pre-Sales team to contribute to sales opportunities and support the conversion of sales prospects.


Experience and Skills

  • Data science experience with expertise in building decisioning or credit risk models using Python or SAS.
  • Applied modelling and analytics experience to lead business decisions.
  • Expertise in credit risk decisioning.
  • Deep coding knowledge in Python with SAS or R.
  • Good stakeholder management skills.
  • Subject matter expert on the mechanics of consumer lending (risk, data usage, outcomes).
  • Knowledge of Cloud / AWS.
  • Product strategy experience desirable but not essential.

Benefits package includes:

  • Hybrid working.
  • Great compensation package.
  • Core benefits include pension, Bupa healthcare, sharesave scheme and more.
  • 25 days annual leave with 8 bank holidays and 3 volunteering days. You can purchase additional annual leave.

Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is a critical part of Experian's DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

#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.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.

Neurodiversity in AI Careers: Turning Different Thinking into a Superpower

The AI industry moves quickly, breaks rules & rewards people who see the world differently. That makes it a natural home for many neurodivergent people – including those with ADHD, autism & dyslexia. If you’re neurodivergent & considering a career in artificial intelligence, you might have been told your brain is “too much”, “too scattered” or “too different” for a technical field. In reality, many of the strengths that come with ADHD, autism & dyslexia map beautifully onto AI work – from spotting patterns in data to creative problem-solving & deep focus. This guide is written for AI job seekers in the UK. We’ll explore: What neurodiversity means in an AI context How ADHD, autism & dyslexia strengths match specific AI roles Practical workplace adjustments you can ask for under UK law How to talk about your neurodivergence during applications & interviews By the end, you’ll have a clearer picture of where you might thrive in AI – & how to set yourself up for success.