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- Tasks: Join a dynamic team to develop predictive models and support loss forecasting.
- Company: A tech-enabled financial services organisation focused on credit risk modelling.
- Benefits: Enjoy hybrid working, on-site parking, and a collaborative team environment.
- Why this job: Make an immediate impact while gaining hands-on experience in data science and finance.
- Qualifications: Degree in a numerate subject and 1-2 years of relevant experience preferred.
- Other info: Must commute to Sevenoaks 3 days a week; driving licence is ideal.
The predicted salary is between 28800 - 43200 £ per year.
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 a Credit Risk Analyst / Data Scientist to 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
- Developing predictive models such as scorecards and machine learning models for customer acquisitions and collections
- Supporting loss forecasting for both new business and the existing portfolio
- Exploring new data sources and modelling techniques to improve performance and accuracy
- Working with tools like Python, T SQL, and Excel to manage data workflows and build solutions
- Collaborating across departments with teams in credit risk, finance, capital markets, and operations
- Monitoring model performance and contributing to regular validation and compliance reporting
What you’ll need?
- A degree, or strong mathematical ability, in a numerate subject such as Mathematics, Statistics, Data Science, Economics, or Physics
- 1 to 2 years of experience in a Financial data driven environment, or strong academic project experience
- Familiarity with modelling techniques like 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 in Python/R, AWS or 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)
Credit Risk Analyst / Data Scientist employer: Eden Smith Group
Contact Detail:
Eden Smith Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Credit Risk Analyst / Data Scientist
✨Tip Number 1
Familiarise yourself with the specific tools mentioned in the job description, such as Python, T-SQL, and Excel. Consider taking online courses or working on personal projects that allow you to demonstrate your skills in these areas, as practical experience can set you apart from other candidates.
✨Tip Number 2
Network with professionals in the credit risk and data science fields. Attend industry meetups or webinars to connect with people who work in similar roles. This can provide you with valuable insights into the role and may even lead to referrals.
✨Tip Number 3
Prepare to discuss your problem-solving approach during interviews. Be ready to share examples of how you've tackled data-related challenges in the past, whether through academic projects or previous work experience, as this will showcase your analytical mindset.
✨Tip Number 4
Since commuting is a requirement, ensure you have a reliable plan for getting to the office in Sevenoaks. If you own a car, highlight your ability to commute easily in your conversations, as this shows your commitment to the role and the company.
We think you need these skills to ace Credit Risk Analyst / Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in credit risk analysis and data science. Emphasise any projects or roles where you've used predictive modelling, machine learning, or data analysis tools like Python and T-SQL.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data science and finance. Mention specific skills that align with the job description, such as your familiarity with modelling techniques and your problem-solving mindset.
Highlight Your Communication Skills: Since the role requires explaining data insights to both technical and non-technical audiences, include examples in your application that demonstrate your ability to communicate complex information clearly.
Show Willingness to Learn: Express your eagerness to learn new tools and techniques, such as AWS or model deployment. This shows that you are adaptable and ready to grow within the role.
How to prepare for a job interview at Eden Smith Group
✨Showcase Your Technical Skills
Be prepared to discuss your experience with tools like Python, T-SQL, and Excel. Highlight any projects where you've developed predictive models or worked with machine learning techniques, as this will demonstrate your capability in a data-driven environment.
✨Demonstrate Problem-Solving Abilities
Prepare examples of how you've approached complex problems in the past. Discuss your thought process and the steps you took to arrive at a solution, especially in relation to data analysis or risk assessment.
✨Communicate Clearly
Practice explaining technical concepts in simple terms. Since you'll need to communicate insights to both technical and non-technical audiences, being able to convey your ideas clearly will be crucial during the interview.
✨Express Your Willingness to Learn
Show enthusiasm for continuous learning, especially regarding new technologies and methodologies in data science. Mention any relevant courses or self-study you've undertaken, particularly in areas like AWS or model deployment.
