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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 offers 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.
- Use 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 in London employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Credit in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your predictive models and machine learning projects. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your SQL and Python skills. Be ready to discuss your experience with credit risk models and how you've used machine learning techniques in past projects.
✨Tip Number 4
Don't forget to apply through our website! We love seeing applications come directly from candidates who are excited about joining our team. It shows initiative and enthusiasm!
We think you need these skills to ace Data Scientist - Credit in London
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 and machine learning techniques, especially in credit risk. 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 this role and how your background makes you a perfect fit. Don’t forget to mention any relevant projects or achievements that showcase your expertise.
Showcase Your Technical Skills: Since SQL and Python are essential for this role, make sure to highlight your proficiency in these areas. We love seeing specific examples of how you've used these skills in past projects, 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 shows us you’re keen on joining our team!
How to prepare for a job interview at Harnham
✨Know Your Models
Make sure you brush up on your knowledge of predictive models, especially in credit risk. Be ready to discuss specific models you've developed and the machine learning techniques you've used. This will show that you not only understand the theory but also have practical experience.
✨SQL and Python Proficiency
Since SQL and Python are essential for this role, we recommend you prepare to demonstrate your skills in these languages. Consider bringing along a project or two where you’ve used them effectively, as this can really impress your interviewers.
✨Collaboration is Key
This role involves working closely with Credit and Product teams, so be prepared to talk about your experience collaborating across departments. Share examples of how you’ve worked with others to enhance model performance and profitability.
✨Stay Current with Trends
The FinTech space is always evolving, so it’s crucial to stay updated on the latest trends in machine learning and credit risk. We suggest discussing any recent developments or innovations you’ve come across, as this shows your passion for the field and your commitment to continuous learning.