At a Glance
- Tasks: Build and maintain machine learning pipelines for pricing models in a dynamic environment.
- Company: Join Hastings Direct, a leading digital insurance provider with a focus on innovation.
- Benefits: Enjoy hybrid work, competitive salary, and opportunities for professional growth.
- Other info: Collaborate with diverse teams in a supportive and inclusive workplace.
- Why this job: Make an impact by turning data science into reliable production workflows.
- Qualifications: Strong Python and SQL skills, with a passion for machine learning and engineering.
The predicted salary is between 49500 - 60500 £ per year.
Unfortunately we are unable to offer sponsorship for this position
Welcome to Hastings Direct We're a digital insurance provider with a clear strategy to become the best and biggest player in the UK market.
As a company, we've made huge investments in our technology, pricing, data and analytics capabilities over the past few years, along with nurturing our 4Cs culture and substantial investment in our people.
And as a Finance team, we're doing exactly the same - building a market leading finance technology platform, investing in our team and our approach to leadership development, with a real focus on commercially adding value to the business.
The fact you're now reading this job advert means we've tempted you to find out more about #lifeat HD. If you like what you see, we hope you'll consider joining our team.
We have high standards and understand some people may not apply for jobs unless they feel they tick every box.
If you're excited about joining us and think you have some of what we are looking for, even if you're not 100% sure, we would love to hear from you.
Role Purpose
We're looking for an MLOps Engineer to help turn pricing models and data science work into reliable production workflows.
You’ll work with Pricing, Data Science, Data Engineering and ML Engineering teams to build pipelines that are easier to test, release, monitor and maintain.
The role is hands‑on, with a focus on Python, SQL, automation, good engineering practice and controlled delivery in a regulated environment.
You’ll own defined MLOps components and pipelines, while working with senior colleagues on wider standards, architecture and governance.
- What you’ll do
- Build, improve and maintain machine learning pipelines used within Market Pricing.
- Productionise Python‑based models, notebooks and data science workflows.
- Help move models from development into repeatable, tested and documented production processes.
- Improve how model workflows are tested, released, monitored and maintained.
- Investigate issues across data, model and pipeline workflows.
- Automate manual steps where this improves quality, speed or control.
- Support good engineering practices, including Git, code review, testing and documentation.
- Make sure pipelines and model workflows are traceable, auditable and safe to change.
- Work closely with Pricing, Data Science, Data Engineering, ML Engineering and governance stakeholders.
- Technology and ways of working
You’ll work in a modern data and machine learning environment. The role is likely to involve:
- Python, including libraries such as Pandas, Num Py and scikit‑learn.
- SQL and large structured datasets.
- Cloud data platforms such as Snowflake, Databricks or similar.
- Git‑based version control and code review.
- CI/CD and automated testing using tools such as Azure Dev Ops, Git Hub Actions or similar.
- Model deployment, monitoring, versioning and governance.
- Reusable engineering patterns for production machine learning.
You do not need experience with every tool listed.
Strong Python, SQL, engineering fundamentals and a willingness to work across data science and production workflows are most important.
- What we’re looking for
- Strong Python skills and experience building data or machine learning workflows.
- Good SQL skills and confidence working with structured datasets.
- Experience building reliable, reusable and maintainable code or pipelines.
- Understanding of machine learning fundamentals, especially supervised learning.
- Experience with Git, code review, testing and technical documentation.
- Exposure to cloud‑based data or engineering environments.
- Good problem‑solving skills and attention to detail.
- Clear communication skills, with the ability to explain technical ideas to different audiences.
- Comfortable working with data scientists, analysts, engineers and business stakeholders.
- A practical focus on quality, reliability, governance and maintainability.
- Nice to have
- Hands‑on experience with cloud platforms such as Azure, AWS or GCP.
- Exposure to modern data platforms such as Snowflake, Databricks, Spark or similar.
- Experience with MLOps practices such as model deployment, monitoring, versioning or model registries.
- Exposure to workflow orchestration or deployment tools such as Airflow, MLflow, Azure Dev Ops, Git Hub Actions or similar.
- Experience in pricing, insurance, financial services or another regulated environment.
- Understanding of model governance, responsible AI or explainability.
The interview process
- Recruiter screening call
- Intro with Hiring manager
- Interview with hiring team - Case study
- Final chat with business leader
As a Disability Confident employer, we're committed to ensuring our recruitment processes are fully inclusive - what this means to you is if you're applying for a job with us, you'll have fair access to support and adjustments throughout your recru
#J-18808-Ljbffr
MLOps Engineer in Bexhill-on-Sea employer: hastingsdirect
Hastings Direct is an exceptional employer, offering a vibrant work culture that prioritises the well-being of its employees through the 4Cs framework. Located in the picturesque Bexhill office by the seafront, employees enjoy a flexible hybrid working model, competitive salary, and extensive training opportunities that foster personal and professional growth. Join us to be part of a dynamic team dedicated to delivering outstanding customer service while contributing to our ambitious goals in the lending market.
StudySmarter Expert Advice🤫
We think this is how you could land MLOps Engineer in Bexhill-on-Sea
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like hastingsdirect!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like MLOps Engineer at hastingsdirect.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like hastingsdirect.
✨Apply Directly through Our Website
When you find a suitable opening like MLOps Engineer at hastingsdirect, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace MLOps Engineer in Bexhill-on-Sea
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at hastingsdirect, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at hastingsdirect. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at hastingsdirect
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at hastingsdirect!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
