Policy Expert – Senior MLOps / Python Engineer
🚀 We’re on a mission to make: The most successful insurance disruptor people want to stay with for life
Are you ready to transform the insurance industry with innovative technology? At Policy Expert, we are on a mission to revolutionize Home, Pet, and Motor insurance, making it clear, fair, and great value for customers. Since our inception in 2011, our breakthrough thinking and proprietary tech, have won us over 1.5 million customers and the title of the UK’s No.1-rated home insurance provider for 9 years. 🏆
Hear from our team about what it's like working at Policy Expert ✨
About our Engineering Team:
We have around 120 engineers out of roughly 600 people in total - and we have big ambitions. There are many interesting challenges ahead, and we're happy for people to move between teams or to specialise, whatever you prefer. As an engineer here you'd be able to work directly with anyone across the company, and we run regular knowledge-sharing sessions, so you’ll learn heaps about everything from how insurance works to effective communication.
Your day-to-day
We are seeking a Senior Data Engineer or Python Engineer to join our cross-functional team of data engineers, data scientists and ML engineers. This team is focused on addressing the strategic market model challenge for our company, which aims to ensure that our quoted prices for home insurance are as competitive as possible.
The ideal candidate will have strong experience in designing, implementing, and optimising data pipelines and systems. You will play a pivotal role in architecting and managing scalable data solutions to support our machine learning models and collaborate with cross-functional teams to integrate these solutions into our product offerings.
- Develop and maintain scalable data pipelines and systems, with a focus on deployment via AWS.
- Implement MLOps frameworks to streamline the lifecycle of our models, ensuring robust data processing, deployment, and monitoring.
- Collaborate with data scientists and product teams to translate business needs into effective data strategies.
- Optimise data processing workflows using tools like Spark, Docker, and cloud-native solutions.
- Mentor and educate team members on data engineering and MLOps best practices.
- Stay current with advancements in data engineering and MLOps, advocate for their integration, and lead the evaluation of tools to enhance workflows.
You should apply if:
- Degree in Computer Science, Information Science, Data Engineering, or a related quantitative field.
- 3+ years of experience in developing and deploying scalable data pipelines to production environments.
- Extensive experience writing production-grade Python code, with a strong understanding of data processing frameworks and ideally familiar with machine learning frameworks such as Scikit-learn.
- Experience with cloud environments (AWS preferred), microservices and implementing MLOps best practices.
- Experience of mentoring more junior engineers.
- Knowledge of the insurance industry would be an advantage but not essential.
Benefits:
📍 This role will be based in our London office in a 50/50 Hybrid mode.
💸 Generous Pension contribution scheme
🏥 Private medical & Dental cover
📚 Learning budget of £1,000 a year + Study leave (with encouragement to use it)
😁 Enhanced maternity & paternity
🚉 Travel season ticket loan
🎟️ Access to a wide selection of London O2 events and use of a Private Lounge
🌈 Employee Wellbeing Programme
What We Stand for and Next Steps “We pride ourselves on being an equal opportunity employer. We treat all applications equally and recruit based solely on an individual’s skills, knowledge, and experience. The quality and growing diversity of our team is a testament to this commitment”
At Policy Expert, we are committed to fostering an inclusive and supportive environment for all candidates. If you require any reasonable adjustments during the interview process to accommodate your needs, please do not hesitate to let us know. We are dedicated to ensuring every candidate has an equal opportunity to succeed and will work with you to provide the necessary support.
We aim to be in touch within 14 working days of your application – you will be notified if successful or unsuccessful. Please be encouraged to apply even if you do not meet all the requirements.
Useful links:
Glassdoor | Trust Pilot | Best Companies
