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For Companies At a Glance
- Tasks: Develop predictive models using innovative machine learning techniques to enhance credit risk strategies.
- Company: Dynamic and fast-paced lender with a focus on growth and impact.
- Benefits: Competitive salary, pension scheme, private medical care, and equity options.
- Other info: Fast-paced environment with opportunities to work on multiple projects.
- Why this job: Join a successful team and make a real difference in the FinTech space.
- Qualifications: Experience in predictive modelling, SQL, Python, and machine learning techniques.
The predicted salary is between 55000 - 65000 £ per year.
This business is a dynamic and fast-paced lender seeking a driven and experienced individual to join their team in building out predictive models using cutting-edge Machine Learning techniques. This role is an opportunity to be part of a successful company that is continuing to grow while driving impact in your work at the forefront of the market.
THE ROLE
- Work across a range of credit models within the business, predominantly scorecards and broader decisioning models.
- Using innovative machine learning techniques to further enhance the model suite and drive profitability across the business.
- Own the deployment and implementation of predictive models across the product suite.
- Work closely with the Credit and Product teams to enhance performance and profitability by collaborating on strategies and model enhancements.
YOUR SKILLS AND EXPERIENCE
- Essential to have experience developing predictive models, ideally within credit risk.
- SQL and Python experience is essential.
- Essential to have experience using Machine Learning techniques to develop non-linear models.
- Experience in a fast-paced environment and ability to work across multiple projects, in a FinTech.
SALARY AND BENEFITS
- Base salary from £55-65,000.
- Company pension scheme.
- Private medical care.
- Equity scheme.
Data Scientist - Credit employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Credit
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those working in credit risk or data science. A friendly chat can lead to insider info about job openings and even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your predictive models and machine learning projects. This is your chance to demonstrate what you can do beyond just a CV.
✨Tip Number 3
Prepare for interviews by brushing up on your SQL and Python skills. Be ready to discuss your experience with non-linear models and how you've used machine learning techniques in past projects.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Data Scientist - Credit
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role. Highlight your experience with predictive models, SQL, and Python. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about credit risk and how your background in machine learning can drive profitability. Let us know what excites you about this opportunity!
Showcase Relevant Projects: If you've worked on any projects that involved credit models or machine learning techniques, make sure to mention them. We love seeing real-world applications of your skills, so don’t hold back!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Harnham
✨Know Your Models
Make sure you can discuss the predictive models you've developed in detail. Be ready to explain your approach, the machine learning techniques you used, and how they impacted profitability. This shows you're not just familiar with the theory but have practical experience.
✨Brush Up on SQL and Python
Since SQL and Python are essential for this role, ensure you're comfortable discussing your experience with both. You might be asked to solve a problem or explain a piece of code, so practice common queries and Python functions related to data manipulation and analysis.
✨Understand the Business
Research the company’s credit products and their market position. Being able to discuss how your work can enhance their product suite will demonstrate your interest and understanding of their business model, making you a more attractive candidate.
✨Prepare for Scenario Questions
Expect questions that assess your ability to work in a fast-paced environment. Think of examples from your past experiences where you successfully managed multiple projects or adapted to changing priorities, as this is crucial in a dynamic FinTech setting.