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- Tasks: Develop Python rating engines and streamline processes in Pricing & Analytics.
- Company: Leading UK insurance firm with a supportive and collaborative culture.
- Benefits: Competitive salary, performance bonuses, and flexible working options.
- Why this job: Join a dynamic team and make a real impact in the insurance industry.
- Qualifications: Strong logical reasoning, relevant education, and teamwork skills.
- Other info: Enjoy a hybrid work model with excellent career growth opportunities.
The predicted salary is between 48000 - 72000 £ per year.
A leading insurance firm in the UK seeks a Senior Machine Learning Operations Engineer. This role involves developing Python rating engines and facilitating efficient processes within the Pricing & Analytics department.
The ideal candidate will have strong logical reasoning, relevant educational background, and collaborative skills to enhance team performance.
Competitive salary, performance-based bonuses, and flexible working options available in a supportive environment.
Lead ML Ops Engineer: Scale Python Rating Engines (Hybrid) employer: AXA Group
Contact Detail:
AXA Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead ML Ops Engineer: Scale Python Rating Engines (Hybrid)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working in ML Ops or at insurance firms. A friendly chat can open doors and give you insights that might just land you that interview.
✨Tip Number 2
Show off your skills! If you've got a portfolio of projects or contributions to open-source, make sure to highlight them. We want to see how you’ve tackled real-world problems with Python and ML.
✨Tip Number 3
Prepare for the technical interview! Brush up on your Python skills and be ready to discuss your experience with rating engines. We know it can be daunting, but practice makes perfect!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take that extra step!
We think you need these skills to ace Lead ML Ops Engineer: Scale Python Rating Engines (Hybrid)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python and ML Ops. We want to see how your skills align with developing rating engines, so don’t hold back on showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re the perfect fit for the role and how your collaborative skills can enhance our team’s performance in the Pricing & Analytics department.
Showcase Your Problem-Solving Skills: In your application, give examples of how you've tackled complex problems in the past. We love logical reasoning, so share any experiences that demonstrate your analytical thinking and decision-making abilities.
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 about the process!
How to prepare for a job interview at AXA Group
✨Know Your Python Inside Out
Make sure you brush up on your Python skills, especially in relation to developing rating engines. Be prepared to discuss specific projects where you've implemented Python solutions and how they improved processes.
✨Showcase Your Logical Reasoning
Since strong logical reasoning is key for this role, practice explaining your thought process during problem-solving scenarios. Use examples from your past experiences to illustrate how your reasoning led to successful outcomes.
✨Emphasise Collaboration Skills
This position requires working closely with the Pricing & Analytics team. Be ready to share examples of how you've successfully collaborated with others in previous roles, highlighting your ability to enhance team performance.
✨Understand the Insurance Industry
Familiarise yourself with the insurance sector and how machine learning can be applied within it. Showing that you understand the industry's challenges and opportunities will set you apart as a candidate who is genuinely interested in the role.
