Machine Learning Operations Engineer

Job description

Machine Learning Operations Engineer

Senior Associate

London

Remote

Full Time

Permanent

Ref:002981

Please note we do not provide any work sponsorships.

XPS Group is a leading UK consulting and administration business specialising in the pensions and insurance sectors. At XPS, our vision is to create a vibrant place to work where difference is recognised as a strength and where talented people can flourish and achieve their highest potential.

Our Data Analytics business continues to grow and we are now looking for an experienced and technical Machine Learning (ML) Operations Engineer to join one our offices with hybrid or remote UK working. This is an exciting role and would most likely suit someone with previous experience in a similarrole 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 Phyton, SQL, CI/CD and familiar with Power BI.

A FTSE 250 company, XPS combines expertise and insight with advanced technology and analytics to address the needs of over 1,400 pension schemes and their sponsoring employers on an ongoing and project basis. We undertake pensions administration for over one million members and provide advisory services to schemes and corporate sponsors in respect of schemes of all sizes, including 88 with assets over £1bn. We also provide wider ranging support to insurance companies in the life and bulk annuities sector.

Our people drive our success and as an XPS employee you can bring your whole self to work - Everyone is treated equally and with respect. We will provide you with the support and training you need to grow and be at your very best. It’s about inclusion and diversity, ensuring all our people feel included, that they belong to XPS and that they’re happy. Above all, it’s about ensuring everyone has a voice and feels valued. Because they are.

The Team

XPS Analytics is a specialist and multi-disciplinary team consisting of actuaries, data scientist 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.

The Role

As a Machine Learning Operations Engineer with XPS you will:

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. Identify appropriate machine learning algorithms and apply them to enhance predictions, automate decision-making processes, and improve client offerings.

Machine Learning Operations.Responsible for designing, deploying, maintaining and refining statistical and machine learning models using Azure ML. Optimize model performance and computational efficiency. Ensure that applications run smoothly and handle large-scare data efficiently. Implement and maintain monitoring of model drifts, data-quality alerts, scheduled r-training pipelines.
Data Management and Preprocessing.Collect, clean and preprocess large datasets to facilitate analysis and model training. Implement data pipelines and ETL processes to ensure data availability and quality.
Software Development.Write clean, efficient and scalable code in Python. Utilize CI/CD practices for version control, testing and code review.
Work closely with actuarial analysts, actuarial modelling team (AMT) and other colleagues in XPS to integrate data science findings into practical advice and strategies.
Stay abreast of new trends and technologies in Data Science technologies and pensions to identify opportunities for innovation.
Provide training and support to other team members on using machine learning tools and understanding analytical techniques.
Interpret and explain machine learning concepts and findings to other members of the analytics team and non-technical stakeholders within XPS.

Your profile

Essential Criteria

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 visualization and reporting tools, ideally PowerBI.
Good written and verbal communication and interpersonal skills. Ability to convey technical concepts to non-technical stakeholders.
Experience in the pensions or similar regulated financial services industry is highly desirable.
Experience in working within a multidisciplinary team would be beneficial.

What we offer:

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We offer an attractive reward package, typical benefits can include:

Competitive salary

Participation in annual discretionary Bonus Scheme
25 days holiday plus flexibility to buy or sell holiday
Flexible Bank holidays
Pension scheme, matching contribution structure
Healthcare cash plan
Flexible Benefits Scheme to support you in and out of work, helping you look after you and your family covering Security & Protection, Health & Wellbeing, Lifestyle
Life Assurance cover, four times basic salary
XPS Rewards (offers High Street discounts and savings from retailers and services providers as well as offers available via phone)
Employee Assistance Programme for you and your household
Access to a digital GP service
Paid volunteering day when participating in Company organised events
Staff referral scheme when you introduce a friend to XPS 

What next:

If you feel XPS could be the next step on your career ladder, please apply directly via the links provided and we look forward to learning more about you. We will consider all applicants and respond swiftly. 

Please discuss with the recruitment team, via phone or email, if you require any adjustments to the recruitment process. For example, we can provide materials in an alternative format, or give you extra time in interviews or tests.

If you do not feel ready to apply or still have questions, please email us by clicking 

The successful candidate will need to demonstrate the following requirements:

Right to Work confirmation

DBS Disclosure check
Employment or educational references covering five years
Satisfactory credit check

We continuously strive to build an inclusive workplace where all forms of diversity are valued, including age, background, disability, gender, gender identity, gender expression, race, religion or sexual orientation.

Please note we reserve the right to close our vacancies early and we only accept CVs direct from candidates or our preferred supplier list.

XPS try wherever possible to respond to all applicants if for any reason you have not heard from us within 28 days of your application, please assume you have been unsuccessful on this occasion.