Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design machine learning models and analyse financial datasets in a fast-paced environment.
- Company: Join a rapidly growing FinTech start-up revolutionising credit decisioning and lending platforms.
- Benefits: Enjoy a competitive day rate, hybrid work options, and potential for contract extension.
- Other info: Experience in a start-up is preferred; immediate start available.
- Why this job: Be part of an innovative team making a real impact in the finance industry.
- Qualifications: 3+ years as a Data Scientist with strong Python and SQL skills; degree in a related field.
The predicted salary is between 48000 - 72000 £ per year.
Location: London (Hybrid – 2-3 days/week onsite)
Contract Length: 6 months initially (with high likelihood of extension)
Type: Contract
Day Rate: Competitive – Dependent on Experience
Start Date: ASAP / July start preferred
We are representing a confidential FinTech start-up based in London that has seen double-digit growth over the past 5 years . Founded by former investment banking and tech leaders, the company specialises in automated credit decisioning, embedded finance, and next-gen lending platforms .
As part of this expansion, they’re looking for an experienced Data Scientist to join their fast-paced, agile environment on a 6-month hybrid contract .
Key Responsibilities:
- Design and deploy machine learning models for risk scoring, customer segmentation, and product optimisation
- Analyse large financial datasets to uncover trends and support product and credit teams
- Develop custom statistical models for portfolio analysis and performance forecasting
- Collaborate cross-functionally with engineering, product, and analytics teams
- Contribute to scalable data pipeline and feature store development
Requirements:
- 3+ years of experience as a Data Scientist in a commercial setting
- Strong skills in Python, SQL , and machine learning libraries (e.g., scikit-learn, XGBoost, etc.)
- Familiarity with cloud platforms (e.g., AWS, GCP) and version control (e.g., Git)
- Experience working with financial or transactional data is a plus
- Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Mathematics, or a related field
- Prior experience in a start-up or scale-up preferred
Data Scientist employer: Fruition Group
Contact Detail:
Fruition Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Familiarise yourself with the specific machine learning libraries mentioned in the job description, such as scikit-learn and XGBoost. Having hands-on experience with these tools will not only boost your confidence but also demonstrate your technical proficiency during discussions.
✨Tip Number 2
Since the role involves analysing large financial datasets, consider brushing up on your knowledge of financial concepts and data analysis techniques. This will help you speak more fluently about how your skills can directly contribute to the company's goals.
✨Tip Number 3
Networking is key! Reach out to current or former employees of the company on platforms like LinkedIn. Engaging with them can provide valuable insights into the company culture and expectations, which you can leverage during your conversations.
✨Tip Number 4
Prepare to discuss your experience with cloud platforms like AWS or GCP. If you have any projects that showcase your ability to work with these technologies, be ready to highlight them, as they are crucial for the role.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience as a Data Scientist, particularly in areas like machine learning, Python, and SQL. Use keywords from the job description to ensure your application stands out.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data science and your understanding of the FinTech industry. Mention specific projects or experiences that align with the company's focus on automated credit decisioning and embedded finance.
Showcase Technical Skills: In your application, emphasise your proficiency in machine learning libraries and cloud platforms. Provide examples of how you've used these skills in previous roles, especially in relation to financial datasets.
Highlight Collaborative Experience: Since the role involves cross-functional collaboration, include examples of how you've worked with engineering, product, or analytics teams in the past. This will demonstrate your ability to thrive in a fast-paced, agile environment.
How to prepare for a job interview at Fruition Group
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, SQL, and machine learning libraries. Bring examples of projects where you've successfully deployed models or analysed large datasets, as this will demonstrate your hands-on expertise.
✨Understand the FinTech Landscape
Familiarise yourself with the latest trends in FinTech, especially around automated credit decisioning and embedded finance. This knowledge will help you engage in meaningful conversations about the company's products and how your skills can contribute.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities. Prepare to discuss how you would approach designing a machine learning model for risk scoring or customer segmentation, as these are key responsibilities of the role.
✨Highlight Collaboration Experience
Since the role involves working cross-functionally, be ready to share examples of how you've collaborated with engineering, product, and analytics teams in the past. Emphasising your teamwork skills will show that you're a good fit for their agile environment.