Senior Credit Risk Analyst (Credit Limit Strategy) | £40k -£55k + Bonus & Awesome Benefits

Skillful
Leicester
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Fraud Analyst

Manager - Credit Analytics

Manager - Credit Analytics

Quantitative Software Developer

eDiscovery Executive / Senior Executive

Senior Data Analyst / Business Analyst

Role: Senior Credit Risk Analyst - Customer ManagementLocation: Leicester – 1 day a week in office Salary: £40,000 -£55,000 + Bonus and great benefits!Love working in Credit Risk butfrustrated with the slow pace, red tape and being pigeon-holed intoa certain area? Then this is the company for you.You will bejoining a FTSE 100, global household name retailer who have a £1.3billion credit portfolio and a customer base of over 3 million butjoin a small, close knit and friendly team.It’s a fantasticopportunity to work to join a growing Credit and Risk Analyticsteam who are responsible for analysing all aspects of our theircredit portfolio and use their vast data to drive insight on howthey can optimise their customer proposition and business profit.You’ll be at the heart of understanding their 3 million creditcustomers and designing, testing and implementing strategy changesto help grow the business.They offer comprehensive, tailoredtraining, a chance for you to work across any area of the creditrisk lifecycle you like and even move teams internally to gainexperience in different business areas. People have joined themfrom some of the biggest and most well-known financial companiesdue to their welcomed change of pace (it has taken them 9 monthsfrom idea generation to launch of a brand-new product!), the familyfeel culture and the chance to really make a difference.If you’reexcited about using data to drive real business impact, this roleis a great place to develop your career within a growing businessand well-known brand!Anyway, the role!This is a brilliantopportunity for someone who has great data analysis skills and areal curiosity about solving business problems. You’ll enjoygetting stuck into complex problems, confidently analysing a rangeof data using industry standard tools (e.g. SQL, SAS, Excel,PowerBI) and working on cross functional projects to deliver greatproducts for our customers.You will:Translate information intogenuine insight that can be used to make informed businessdecisionsComment on trends, adding value through contributing ideasand solutions to any problems or opportunities identified.Identifyrisks and opportunities in the current processes and rules throughcomplex analysis, using multiple data sources.Serve as the experton credit risk and data, while best representing the commercialvalue and regulatory aspects of lending activity.Build and presentreporting and strategy recommendations relating to credit &risk at internal and external meetings where required.So, if youhave:Experience of working in a data analyst positionProven trackrecord of using information to provide business insightA history ofusing data strategicallyA demonstrable track record of analysingand reviewing data coupled with an ability to then makerecommendations to gain buy in and implement changeExperience ofworking with coding platforms such as SQL/SAS/Python or similarAnatural problem solver with a proven ability to work logicallyYouwill have an eye for detail combined with the drive to get underthe skin of complex business challenges, joining the dots acrossmultiple sources of insightEnjoy working with a diversemulti-discipline team to deliver results at paceStrong verbal andwritten communication skillsThen we want to speak with you – and sowill they.We are more than happy to send you a full spec or singtheir praises over a brief call - just let us know what you /

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Job-Hunting During Economic Uncertainty: Data Science Edition

Data science has become essential for modern businesses, enabling data-driven decisions that enhance efficiency, profitability, and strategic foresight. From predictive analytics in finance to recommendation engines in retail, data scientists sit at the crossroads of statistics, programming, and domain expertise, building models that translate raw information into tangible insights. Yet, when broader economic forces create uncertainty—through market downturns, shifting investor priorities, or internal budget constraints—data science roles can experience increased scrutiny, competition, and extended hiring cycles. Despite these pressures, data-driven approaches remain crucial to organizations looking to weather challenges and find opportunities in volatile environments. Whether you’re refining advanced machine learning techniques, fine-tuning data pipelines, or collaborating with business stakeholders on dashboards, your skill set is often still in demand. The key is adapting your job search strategy and personal branding to cut through the noise when fewer roles may be available. This article explores: Why economic headwinds affect data science hiring. Actionable strategies to stand out in a tighter job market. Ways to emphasize your technical and soft skills effectively. Techniques to maintain focus and resilience despite potential setbacks. How www.datascience-jobs.co.uk can help you secure the ideal data science position. By combining strategic thinking, polished communications, and adaptability, you can land a fulfilling data science role that leverages your expertise—even if the market feels more demanding.

How to Achieve Work-Life Balance in Data Science Jobs: Realistic Strategies and Mental Health Tips

Data science has quickly emerged as one of the most influential fields in the modern workplace, shaping how businesses make critical decisions and expanding our understanding of everything from consumer behaviour to public health trends. As the global demand for data insights continues to rise, companies of all sizes are seeking professionals who can effectively harness analytics and machine learning to drive innovation. Yet, this promise of limitless opportunity comes with significant challenges. Data scientists often grapple with large volumes of complex data, tight project deadlines, cross-functional collaboration, and constant upskilling. Amid the excitement of discovering actionable insights and developing high-performing models, many wonder if it’s truly possible to maintain a healthy work-life balance. With the field evolving at breakneck speed, the intensity of these roles can leave even the most passionate data professionals drained and questioning how to protect their personal well-being. This article delves into the reality of high-intensity data science jobs, offering practical guidance on setting realistic expectations and preserving mental health. We’ll look at common pitfalls like burnout and perpetual “always learning” pressure, while also highlighting proven strategies for boundary-setting and effective time management. Whether you’re a seasoned data architect, an aspiring machine learning engineer, or somewhere in between, you’ll find actionable tips to help you manage your career trajectory without sacrificing your personal life.

From Research Labs to Real-World Insights: How Academic Researchers Can Thrive in Data Science

Over the past decade, the data science revolution has swept across industries—retailers predicting shopping habits, hospitals personalising patient treatments, and finance companies detecting fraud in near-real time. This surge in data-driven decision-making has created a pressing need for specialists capable of extracting meaningful insights from complex datasets. As a result, PhD holders and academic researchers are uniquely positioned to bring high-calibre analytical skills to the commercial realm. But transitioning from academia to data science can seem daunting: Where do you begin? How do you communicate your research background in industry-friendly terms? What new tools should you learn? This comprehensive guide, explores the paths, challenges, and strategies for academics making the leap into data science. You’ll discover how to leverage your scholarly expertise, adopt a commercial mindset, and build a career that transforms raw data into actionable insights—fostering innovations across every sector of the economy.