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- Tasks: Lead teams to develop credit risk models and improve operational processes.
- Company: A leading financial wellbeing platform in Greater London.
- Benefits: Hybrid working, generous benefits, and opportunities for professional growth.
- Why this job: Shape strategy and make a real impact in financial wellbeing.
- Qualifications: 5+ years in Data Science with strong leadership and skills in Python and SQL.
- Other info: Join a dynamic team focused on innovation and excellence.
The predicted salary is between 48000 - 72000 £ per year.
A financial wellbeing platform in Greater London is seeking a Data Science Manager to lead the Data Science and Decision Systems teams. The role involves shaping strategy, mentoring, and hands-on project delivery focused on developing credit risk models and enhancing operational processes.
Candidates should have strong leadership experience, over 5 years in Data Science, and proficiency in Python and SQL. This position offers a hybrid working environment and generous company benefits.
Data Science Manager: Credit Risk & Financial Wellbeing in London employer: Salary Finance
Contact Detail:
Salary Finance Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Manager: Credit Risk & Financial Wellbeing in London
✨Tip Number 1
Network like a pro! Reach out to folks 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 data science projects, especially those related to credit risk models. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your Python and SQL skills. Be ready to discuss your past experiences and how they relate to the role. Practice common interview questions to boost your confidence!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Data Science Manager: Credit Risk & Financial Wellbeing in London
Some tips for your application 🫡
Show Your Leadership Skills: Make sure to highlight your leadership experience in your application. We want to see how you've shaped strategies and mentored teams in the past, especially in Data Science.
Demonstrate Technical Proficiency: Since this role requires strong skills in Python and SQL, don’t forget to mention specific projects or experiences where you’ve used these tools. We love seeing practical examples!
Tailor Your Application: Take a moment to customise your CV and cover letter for this role. We’re looking for candidates who understand our mission in financial wellbeing, so make it clear why you’re a great fit.
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 don’t miss out on any important updates from us!
How to prepare for a job interview at Salary Finance
✨Know Your Data Science Stuff
Make sure you brush up on your data science fundamentals, especially around credit risk models. Be ready to discuss your past projects in detail, showcasing your proficiency in Python and SQL. This will demonstrate your technical expertise and how it aligns with the role.
✨Showcase Your Leadership Skills
As a Data Science Manager, leadership is key. Prepare examples of how you've mentored teams or led projects in the past. Highlight your approach to shaping strategy and how you’ve successfully guided your team through challenges.
✨Understand the Company’s Mission
Research the financial wellbeing platform and understand its goals. Be prepared to discuss how your vision for data science can enhance their operational processes. This shows that you’re not just looking for a job, but are genuinely interested in contributing to their mission.
✨Prepare Questions to Ask
Interviews are a two-way street! Prepare insightful questions about the company culture, team dynamics, and future projects. This not only shows your interest but also helps you gauge if the company is the right fit for you.
