At a Glance
- Tasks: Join our Data Science team to work on AI, machine learning, and real-time data integration.
- Company: Dynamic fintech company focused on innovation and collaboration.
- Benefits: Hybrid work, 25 days holiday, gym membership, and wellness budget.
- Other info: One-year graduate scheme with potential for permanent role and career growth.
- Why this job: Make a real impact on financial technology and customer experience.
- Qualifications: Recent graduate in a technical field with Python skills and a passion for fintech.
The predicted salary is between 28000 - 38000 £ per year.
Our Data Science team works across our entire business, from new products to core credit decisioning and user acquisition. You will be exposed to a wide range of projects and gain cross‑functional experience with risk, compliance, underwriting and product teams.
Key Responsibilities
- AI & Machine Learning Development: work directly on our proprietary loan decision platform, Render, contributing to transformer models that improve loan performance.
- Open Banking Integrations and Classification: enhance the transformation of noisy, real‑time transaction data into automated lending decisions.
- Product Development: participate in rapid feature development cycles, with direct impact on customer experience and business outcomes.
- Credit Risk Analytics: analyse how our loan book performs over time, including portfolio monitoring, impairment measurement and risk analytics behind our funding.
- Bi‑annual technical reviews and career progression planning.
- Collaborate with risk, compliance, underwriting and product teams to shape the future of credit.
Qualifications & Skills
- Recent or soon‑to‑be graduate with a degree in a technical or quantitative field (Data Science, Statistics, Mathematics, Engineering, Economics).
- Proficiency in Python or similar programming languages.
- Strong interest in financial technology and the application of AI to real‑world problems.
- Excellent communication skills and ability to work effectively in cross‑functional teams.
- Motivation to learn by doing, with a focus on the commercial impact of technical changes.
Benefits
- Hybrid workplace: 3 days a week in the office.
- 25 days' holiday a year, plus 8 bank holidays.
- Two paid volunteering days per year.
- One month paid sabbatical after 4 years.
- Free gym membership.
- Team wellness budget to support activities such as yoga, tennis or bouldering.
Additional Information
We are an equal‑opportunity employer. The graduate scheme runs for one year, with the possibility of conversion to a permanent role based on performance. Start date is scheduled for Late September – Early October 2026 (TBC).
Graduate Data Scientist employer: Deutsche Bank AG
As a Graduate Data Scientist, you will thrive in a dynamic and innovative environment that champions collaboration across various teams, enhancing your professional growth while working on impactful projects. Our hybrid workplace fosters a healthy work-life balance, complemented by generous benefits such as 25 days' holiday, paid volunteering days, and a wellness budget to support your interests. Join us to not only advance your career in financial technology but also contribute to shaping the future of credit with cutting-edge AI solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Graduate Data Scientist
✨Get in on the Data Science Meetups
Data science is all about community! Join local meetups or workshops related to data science and analytics. It's a fab way to network with industry professionals, learn about the latest trends, and maybe even snag a lead on an upcoming opportunity at companies like Deutsche Bank AG.
✨Show Off Your Projects
As a trainee, showcasing your skills is key. Start a GitHub repository with your projects or analytics problems you've solved. Share them on platforms like Kaggle, and make sure to link them on your LinkedIn. Potential employers, including Deutsche Bank AG, love seeing hands-on experience!
✨Connect with Alumni
Tap into your university's alumni network! Reach out to past graduates who are working in data science roles and see if they'd be willing to chat. They often have great insights into internship openings and can even refer you internally, increasing your chances with companies like Deutsche Bank AG.
✨Find Internships through Portals and Workshops
Keep an eye out for career fairs and workshops specifically targeting data science roles. Many companies, including Deutsche Bank AG, often scout for trainee talent at these events. Plus, applying directly through job portals and company websites can give you an edge!
We think you need these skills to ace Graduate Data Scientist
Some tips for your application 🫡
Show Off Your Data Skills:Make sure to highlight your data-related skills clearly in your CV. If you've worked on any projects using Python or R, be sure to mention them. Also, if you've dabbled in machine learning, include that too—employers love a hands-on learner!
Include Relevant Projects:Since this is a trainee position, listing your university projects or any personal data science projects can really impress. Attach a GitHub link if possible, so Deutsche Bank AG can see your code and your thought process. Practical experience, even if it's academic, can set you apart!
Personalise Your Cover Letter:Use your cover letter to show how passionate you are about data science. Describe why you're excited about the opportunity at Deutsche Bank AG and how the role aligns with your career goals in this dynamic field. We want to see your enthusiasm and potential to grow.
Tailor Your CV for Trainees:Since you’re applying for a trainee position, focus on academic achievements and any relevant coursework in your CV. Don’t sweat the lack of professional experience—your ability to learn and adapt is what counts. Also, make sure to align your CV format with data science norms; keep it clear and concise!
How to prepare for a job interview at Deutsche Bank AG
✨Show Off Your Data Skills
Make sure you're ready to chat about the tools we use in data science, like Python, R, or SQL. Brush up on key concepts like data cleaning, analysis, and visualisation — interviewers often delve into these areas to see how you think and approach problems.
✨Prepare for Practical Assessments
Don't be surprised if you're given a case study or data set to analyse during the interview. We should be prepared to demonstrate how we interpret and present data findings — it's a chance to show off our analytical thinking in real time!
✨Highlight Your Passion for Learning
As a trainee, it’s all about showing your enthusiasm for data science! Share any personal projects, online courses, or relevant experiences. This tells Deutsche Bank AG that we’re eager to grow and develop our skills in this exciting field.
✨Ask Insightful Questions
Use this opportunity to find out more about the team’s projects and tools. Questions like ‘What data challenges are you currently facing?’ can demonstrate our interest while also helping us understand how we might fit into Deutsche Bank AG’s culture and workflow.
