Data Analyst - Credit Risk

Energy Vault
London
8 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

This could not be a better time to join Octopus Energy. We are already recognised as a global leader in the fight to decarbonise the planet by revolutionising what’s possible in energy - including investments in renewable energy supply, renewable energy generation, smart energy networks, EVs, heat pumps, etc. The government's new green initiatives and the recent investment by Al Gore’s Generation Fund will propel us further and faster.

There has never been a more important moment to join our credit risk team. The energy sector is going through a period of once-in-a-generation volatility. Businesses and households are facing higher energy prices than they ever have before. For these reasons we are looking to add to our credit risk team with this new role. This team sits at the heart of everything we do to support customers that are struggling with their bills. We’re unique because we are genuinely a hybrid of a few different skills and mindsets:

1. Data analytics is our core skillset. Everyone in the team is very strong in this area

2. We have a firm understanding of the needs of our customers and the business

3. We work closely with the tech team, because we’re a tech company, so this how we solve customer problems, efficiently at scale

4. We work closely with our operations teams who are the people that speak directly to customers

What you'll do

  • Take ownership of our management of customers who are struggling with their payments
  • Deep dive investigations into data in order to surface insight for decision making
  • Develop our reporting suite through the latest BI tools & technology stack
  • Develop our empathic approaches towards vulnerable customers
  • Create strategies to identify and prevent first party and third party fraud
  • Develop our machine learning models & policies that drive sophisticated decisions
  • Proactively identify new areas of opportunity
  • Challenge the status quo in terms of KPIs, objectives & strategy
  • Communicate complex data concepts effectively and confidently
  • Build great relationships with Data Science, Technology, Finance, Collections, Ops and other stakeholders

What you'll need

  • Excellent SQL skills
  • A drive to solve problems using data
What would be a bonus:
  • Python data science stack (pandas, NumPy, Jupyter notebooks, Plotly/matplotlib, etc)
  • Familiarity with Git
  • Data visualization tool (Tableau, Looker, PowerBI or equivalent)
  • DBT
  • 2-5 years experience of consumer credit risk or collections in the financial services, utilities or telecommunications industries

Why else you'll love it here

  • Wondering what the salary for this role is? Just ask us! On a call with one of our recruiters it's something we always cover as we genuinely want to match your experience with the correct salary. The reason why we don't advertise is because we honestly have a degree of flexibility and would never want salary to be a reason why someone doesn't apply to Octopus - what's more important to us is finding the right octofit!
  • Octopus Energy is a unique culture. An organisation where people learn, decide, and build quicker. Where people work with autonomy, alongside a wide range of amazing co-owners, on projects that break new ground. We want your hard work to be rewarded with perks you actually care about! We won best company to work for in 2022, on Glassdoor we were voted 50 best places to work in 2022 and our Group CEO, Greg has recorded a podcast about our culture and how we empower our people. We’ve also been placed in the top 10 companies for senior leadership
  • Visit our UK perks hub - Octopus Employee Benefits


#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.

Jobs

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

Careers

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.

Jobs

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.

🍪 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.