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- Tasks: Lead a team to develop and deploy innovative ML solutions for risk decisioning.
- Company: Dynamic fintech startup in the UK with a focus on AI-driven financial products.
- Benefits: Competitive salary, growth opportunities, and a fast-paced work environment.
- Why this job: Make a significant impact on customer experience through cutting-edge technology.
- Qualifications: Experience in machine learning and team leadership.
- Other info: Join a diverse data science unit and shape the future of fintech.
The predicted salary is between 48000 - 72000 £ per year.
A dynamic fintech startup in the UK is seeking a Machine Learning Manager to lead their Risk Decisioning team. In this role, you will develop and deploy impactful ML solutions that enhance customer experience through conversational interfaces. You’ll oversee team performance, manage a diverse data science unit, and contribute to shaping the roadmap for AI-driven financial products. This position promises opportunities for growth and significant impact in a fast-paced environment.
ML Engineering Manager, Risk Decisioning Leader employer: cleo
Contact Detail:
cleo Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Engineering Manager, Risk Decisioning Leader
✨Tip Number 1
Network like a pro! Reach out to folks in the fintech space, especially those working with ML and risk decisioning. A friendly chat can open doors and give you insights that might just land you that interview.
✨Tip Number 2
Showcase your skills! Create a portfolio of your ML projects, especially those related to customer experience or financial products. This will not only impress potential employers but also demonstrate your hands-on experience.
✨Tip Number 3
Prepare for the interview by brushing up on your leadership skills. As a manager, you'll need to show how you can guide a diverse team and drive performance. Think of examples from your past experiences that highlight your management style.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for you, and applying directly can sometimes give you an edge. Plus, it’s super easy to keep track of your applications!
We think you need these skills to ace ML Engineering Manager, Risk Decisioning Leader
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in machine learning and risk decisioning. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about fintech and how you can contribute to our team. We love seeing enthusiasm and a clear understanding of our mission.
Showcase Your Leadership Skills: As a Machine Learning Manager, you’ll be leading a diverse team. Highlight any previous leadership experiences and how you’ve successfully managed teams or projects. We’re looking for someone who can inspire and drive results!
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 this exciting opportunity. Don’t miss out on the chance to join our dynamic team!
How to prepare for a job interview at cleo
✨Know Your ML Stuff
Brush up on your machine learning concepts, especially those related to risk decisioning. Be ready to discuss specific algorithms and their applications in fintech. We recommend preparing examples of how you've successfully implemented ML solutions in previous roles.
✨Showcase Leadership Skills
As a manager, you'll need to demonstrate your ability to lead a diverse team. Think about past experiences where you’ve motivated your team or resolved conflicts. We suggest preparing anecdotes that highlight your leadership style and how it aligns with the company’s values.
✨Understand the Fintech Landscape
Familiarise yourself with current trends in fintech, particularly around AI-driven financial products. We encourage you to research the company’s competitors and be ready to discuss how your insights could help shape their roadmap for success.
✨Prepare for Scenario Questions
Expect scenario-based questions that assess your problem-solving skills in real-world situations. We advise practising responses to potential challenges you might face in the role, such as managing team performance or deploying new ML solutions under tight deadlines.
