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- Tasks: Develop cutting-edge credit risk models and translate business challenges into data-driven solutions.
- Company: Join a high-growth fintech transforming consumer finance with innovative technology and data science.
- Benefits: Enjoy a hybrid work model, competitive salary, and a range of corporate perks.
- Why this job: Be part of a market leader, driving strategic decisions and product innovation in a collaborative environment.
- Qualifications: Strong Python and SQL skills, familiarity with credit industry, and a STEM degree from a top university.
- Other info: Opportunity to work autonomously and communicate insights directly to stakeholders.
The predicted salary is between 48000 - 72000 £ per year.
Our client is a high-growth fintech revolutionising consumer finance through cutting-edge technology and data science. Backed by top investors and consistently rated as a market leader, they are transforming the way loans, credit cards, and financial products are delivered - offering customers faster, more transparent, and seamless experiences.
As a Senior Data Scientist, you’ll play a pivotal role in developing proprietary risk models that drive strategic decision-making and product innovation. Working within a multidisciplinary team, you’ll apply advanced machine learning techniques to improve underwriting quality and enhance financial product offerings.
Key Responsibilities- Build and refine credit risk models using state-of-the-art ML techniques.
- Translate business challenges into data-driven solutions.
- Deploy and monitor models autonomously, without reliance on a separate ML engineering team.
- Clearly communicate insights and recommendations to stakeholders.
- Strong Python experience, with knowledge of ML techniques.
- Familiarity with the credit industry, financial products, and data-driven risk modelling.
- Experience across Credit modelling, lending, PoD etc.
- Strong educational background from a top university in a STEM subject.
- A proactive problem solver who thrives in a fast-paced environment.
- Strong communication skills and a collaborative mindset.
- Interest in ML engineering and data engineering.
- Strong SQL skills.
If this role looks of interest to you, please apply below, or reach out to Joseph Gregory.
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist
✨Tip Number 1
Familiarise yourself with the latest trends in credit risk modelling and machine learning techniques. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the fintech industry, especially those working in data science roles. Attend relevant meetups or webinars to gain insights and potentially get referrals that could boost your application.
✨Tip Number 3
Prepare to discuss specific projects where you've successfully built and deployed credit risk models. Be ready to explain your thought process, the challenges you faced, and how you overcame them, as this will demonstrate your hands-on experience.
✨Tip Number 4
Brush up on your SQL skills and be prepared to showcase your ability to manipulate and analyse data effectively. Having practical examples of how you've used SQL in past projects can set you apart from other candidates.
We think you need these skills to ace Senior Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, machine learning techniques, and credit risk modelling. Use specific examples from your past work that demonstrate your ability to build and refine credit risk models.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the fintech industry and how your skills align with the company's mission. Mention your proactive problem-solving abilities and your experience in a fast-paced environment.
Showcase Relevant Projects: If you have worked on projects related to credit modelling or financial products, include them in your application. Describe your role, the techniques you used, and the impact of your work on the project outcomes.
Prepare for Technical Questions: Be ready to discuss your technical skills in Python, SQL, and machine learning during the interview process. Brush up on relevant concepts and be prepared to explain how you've applied them in real-world scenarios.
How to prepare for a job interview at Harnham
✨Showcase Your Technical Skills
As a Senior Data Scientist, you'll need to demonstrate your strong Python and SQL skills. Be prepared to discuss specific projects where you've applied machine learning techniques, and consider bringing along a portfolio of your work to showcase your expertise.
✨Understand the Credit Industry
Familiarise yourself with the credit industry and financial products before the interview. Being able to discuss current trends and challenges in credit risk modelling will show that you are not only technically proficient but also knowledgeable about the field.
✨Prepare for Problem-Solving Questions
Expect to face problem-solving scenarios during the interview. Practice articulating your thought process when tackling complex data challenges, as this will highlight your proactive approach and ability to thrive in a fast-paced environment.
✨Communicate Clearly and Collaboratively
Strong communication skills are essential for this role. Be ready to explain your insights and recommendations clearly to stakeholders. Practising how to convey complex data findings in an understandable way will help you stand out as a collaborative team player.
