At a Glance
- Tasks: Design, build, and optimise machine learning models using Azure ML in a collaborative environment.
- Company: Join XPS Group, a leading UK consultancy with a vibrant culture and diverse talent.
- Benefits: Enjoy competitive salary, flexible working, healthcare plans, and 25 days holiday.
- Other info: Be part of a dynamic team with excellent career growth opportunities.
- Why this job: Make an impact in the pensions sector while working with cutting-edge technology.
- Qualifications: Experience in MLOps, Python, SQL, and CI/CD practices required.
The predicted salary is between 60000 - 75000 £ per year.
At XPS Group we operate a hybrid/flexible working style. We are an equal opportunities employer and positively encourage applications from suitably qualified and eligible candidates regardless of sex, race, disability, sexual orientation, religion or belief. As part of our Disability Confident pledge, we run the ‘Offer an interview’ scheme at XPS. If you have a disability and meet the ‘essential criteria’ described in the person specification for the role being applied for, you are guaranteed an interview.
Job details:
- Contractual hours: 36.25
- Basis: Full time
- Location: London
- Employment Type: Permanent, Full Time
- Grade: Senior Associate/ Consultant
About XPS Group:
XPS Group is a prominent and growing UK consultancy and administration firm within the pensions and insurance sectors. As a FTSE 250 company with over 2000 employees, we leverage expertise alongside advanced technology to serve over 1,400 pension schemes and their sponsors. Our goal is to foster a workplace where diverse talents thrive.
About the Role:
Our Data Analytics business continues to grow, and we are now looking for an experienced and technical MLOps Engineer to join our vibrant London office with hybrid working. This is an exciting role and would most likely suit someone with previous experience in a similar role where they have gained knowledge and experience of designing, building, optimising, deploying and managing business‑critical machine learning models using Azure ML in production environments. You must have good technical knowledge of Python, SQL, CI/CD and be familiar with Power BI.
XPS Analytics is a specialist and multi‑disciplinary team consisting of actuaries, data scientists and developers. Our role in this mission is to pioneer advancements in the field of pensions and beyond, leveraging state‑of‑the‑art technology to extract valuable and timely insights from data. This enables the consultant to better advise Trustees and corporate clients on a wide range of actuarial‑related areas.
Key Responsibilities:
- Model development: Work collaboratively with actuarial analysts to develop machine learning and statistical models to predict outcomes related to pension schemes, such as life expectancy, default risk, or investment returns.
- Machine Learning Operations: Responsible for designing, deploying, maintaining and refining statistical and machine learning models using Azure ML. Optimize model performance and computational efficiency.
- Data Management and Preprocessing: Collect, clean and preprocess large datasets to facilitate analysis and model training.
- Software Development: Write clean, efficient and scalable code in Python. Utilize CI/CD practices for version control, testing and code review.
- Provide training and support to other team members on using machine learning tools and understanding analytical techniques.
Your Profile:
- Previous experience in designing, building, optimising, deploying and managing business‑critical machine learning models using Azure ML in production environments.
- Experience in data wrangling using Python, SQL and ADF.
- Experience in CI/CD and DevOps/MLOps and version control.
- Familiarity with data visualisation and reporting tools, ideally PowerBI.
- Good written and verbal communication and interpersonal skills.
- Experience in the pensions or similar regulated financial services industry is highly desirable.
What We Offer:
Enjoy a competitive salary, annual discretionary bonus, and 25 days’ holiday with buy/sell flexibility. Benefits include pension matching, healthcare plans, life assurance, and retailer discounts. We support our team with a flexible benefits scheme, employee assistance, and digital GP service. Participation in volunteering events is encouraged with paid volunteer days available. Referral bonuses are offered for introducing suitable candidates to XPS.
Benefits Statement:
Any employment offer made will be conditional upon you satisfying DBS Disclosure checks, Employment or educational references, Satisfactory credit checks and eligibility to work in the UK before an offer can be made. XPS Group is not able to provide sponsorship to employees.
MLOps Engineer employer: Xafinity Consulting Ltd
XPS Group is an exceptional employer, offering a vibrant work culture in London that embraces hybrid working and values diversity. With a strong focus on employee growth, we provide competitive salaries, comprehensive benefits, and opportunities for professional development within our innovative Data Analytics team. Join us to be part of a forward-thinking consultancy that champions inclusivity and encourages meaningful contributions to the pensions sector.
StudySmarter Expert Advice🤫
We think this is how you could land MLOps Engineer
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We think you need these skills to ace MLOps Engineer
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!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Xafinity Consulting Ltd. 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!
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✨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!
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✨Get Comfortable with Python and R
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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.