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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 in London employer: cleo
Contact Detail:
cleo Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Engineering Manager, Risk Decisioning Leader in London
✨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 projects! If you've worked on any ML solutions or have experience in enhancing customer experiences, make sure to highlight these in conversations. We want to see how you can bring value to our team!
✨Tip Number 3
Prepare for technical discussions! Brush up on your ML concepts and be ready to discuss how you would approach risk decisioning challenges. We love candidates who can think on their feet and demonstrate their expertise.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows us you're genuinely interested in being part of our dynamic team at this exciting fintech startup.
We think you need these skills to ace ML Engineering Manager, Risk Decisioning Leader in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Machine Learning Manager role. Highlight your leadership experience and any relevant projects you've worked on in risk decisioning or AI-driven products.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about fintech and how your background makes you the perfect fit for our team. Share specific examples of how you've developed impactful ML solutions in the past.
Showcase Your Team Management Skills: Since you'll be overseeing a diverse data science unit, it's crucial to demonstrate your ability to lead and inspire a team. Include examples of how you've successfully managed teams and driven performance in previous roles.
Apply Through Our Website: We encourage you to apply directly through our website for a smoother application process. This way, we can easily track your application and get back to you faster!
How to prepare for a job interview at cleo
✨Know Your ML Fundamentals
Brush up on your machine learning concepts, especially those related to risk decisioning. Be ready to discuss algorithms, model evaluation metrics, and how they apply to financial products. This shows you’re not just a manager but also a technical leader.
✨Showcase Your Leadership Style
Prepare examples of how you've successfully led diverse teams in the past. Highlight your approach to managing performance and fostering collaboration within a data science unit. This will demonstrate your capability to lead the Risk Decisioning team effectively.
✨Understand the Fintech Landscape
Familiarise yourself with current trends in fintech, particularly around AI-driven solutions. Being able to discuss how these trends can enhance customer experience through conversational interfaces will set you apart as a candidate who’s genuinely interested in the industry.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think about challenges you’ve faced in deploying ML solutions and how you overcame them. This will showcase your critical thinking and adaptability in a fast-paced environment.
