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- Tasks: Join a dynamic team to drive machine learning in credit decisions.
- Company: A forward-thinking financial services client focused on data-driven solutions.
- Benefits: Enjoy hybrid work options and competitive salaries with excellent perks.
- Why this job: Be part of an agile, data-driven culture that values innovation and collaboration.
- Qualifications: Strong academic background and 3+ years of data science experience required.
- Other info: Interview process includes a quick test and a take-home task.
The predicted salary is between 43200 - 72000 £ per year.
With recent significant investment and a strong focus on machine learning-driven credit decisions, our FS client is currently expanding their team and looking for talented data scientists to join them.
They offer hybrid and remote-first work, with their engineering and data teams officially based in London but flexible depending on experience level.
Their hiring bar is high, but they foster an incredible data-driven culture, operating in cross-functional agile teams of 5-6 members.
They are particularly interested in candidates with:
✅ A strong academic background (Maths BSc + MSc but open to others)
✅ 3+ years of commercial experience in data science
✅ Strong skills in probability, statistics, and mathematical modelling
✅ Proficiency in Python, Pandas, NumPy, SciPy, R, and other scientific computing tools
✅ Experience implementing data-driven solutions in a production environment
✅ Hands-on expertise with statistical modelling, feature engineering, and A/B testing
✅ Experience with machine learning model development, including Bayesian methods and stochastic processes
✅ Understanding of financial modelling concepts, deterministic cash flow calculations (a plus, but not required)
✅ A research-driven mindset, with the ability to translate complex mathematical concepts into real-world applications
They are offering competitive salaries plus excellent benefits. The interview process includes a quick test, a take-home task, and discussions with the hiring team.
Would love to share more details—let me know if you’d be open to a quick chat!
Data Scientist employer: DeepRec.ai
Contact Detail:
DeepRec.ai Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Make sure to brush up on your statistical modeling and machine learning techniques. Since the role emphasizes Bayesian methods and stochastic processes, being able to discuss these topics confidently during interviews will set you apart.
✨Tip Number 2
Familiarize yourself with the company's data-driven culture and agile team structure. Understanding how cross-functional teams operate can help you demonstrate your ability to collaborate effectively during the interview process.
✨Tip Number 3
Prepare for the quick test and take-home task by practicing coding challenges in Python and using libraries like Pandas and NumPy. This hands-on experience will help you feel more confident and perform better.
✨Tip Number 4
If you have any experience with financial modeling or deterministic cash flow calculations, be ready to discuss it. Even though it's a plus and not required, showing knowledge in this area can give you an edge over other candidates.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Highlight Relevant Experience: Make sure to emphasize your 3+ years of commercial experience in data science. Detail specific projects where you implemented data-driven solutions, showcasing your hands-on expertise with statistical modeling and machine learning.
Showcase Technical Skills: Clearly list your proficiency in Python, Pandas, NumPy, SciPy, R, and any other scientific computing tools. Provide examples of how you've used these tools in past projects, especially in relation to A/B testing and feature engineering.
Demonstrate Academic Background: If you have a strong academic background in Maths (BSc + MSc), make sure to mention it prominently. If your background is different but relevant, explain how your education has prepared you for the role.
Prepare for the Interview Process: Since the interview process includes a quick test and a take-home task, practice common data science problems and be ready to discuss your approach to solving them. Familiarize yourself with Bayesian methods and stochastic processes as they are key components of the role.
How to prepare for a job interview at DeepRec.ai
✨Showcase Your Technical Skills
Be prepared to discuss your proficiency in Python, Pandas, NumPy, and other scientific computing tools. Highlight specific projects where you implemented data-driven solutions and how you used statistical modeling and A/B testing.
✨Demonstrate Your Problem-Solving Ability
During the interview, focus on your experience with machine learning model development. Be ready to explain your approach to Bayesian methods and stochastic processes, and how you've applied these concepts in real-world scenarios.
✨Prepare for the Quick Test
Since the interview process includes a quick test, practice common data science problems and algorithms beforehand. Brush up on your probability and statistics knowledge to ensure you're ready to tackle any questions that come your way.
✨Emphasize Your Research-Driven Mindset
The company values candidates who can translate complex mathematical concepts into practical applications. Prepare examples from your past work where you successfully bridged the gap between theory and practice, showcasing your analytical thinking.
