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- Tasks: Develop and optimise machine learning models for pension schemes using Azure ML.
- Company: XPS Group is a leading UK consulting firm in pensions and insurance, focused on innovation.
- Benefits: Enjoy flexible working, competitive salary, healthcare plans, and 25 days holiday plus more!
- Why this job: Join a vibrant team where diversity is celebrated and your skills can truly shine.
- Qualifications: Experience with Azure ML, Python, SQL, and CI/CD practices is essential.
- Other info: Remote work options available; we value inclusion and support your growth.
The predicted salary is between 43200 - 72000 ÂŁ per year.
Join to apply for the Machine Learning Operations Engineer role at XPS Group
Join to apply for the Machine Learning Operations Engineer role at XPS Group
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.
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
Find out more about Life at XPS
Find out more about Our People Approach
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 here
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.
Seniority level
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Seniority level
Mid-Senior level
Employment type
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Employment type
Full-time
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Job function
Engineering and Information Technology
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Machine Learning Operations Engineer (London) employer: XPS Group
Contact Detail:
XPS Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Operations Engineer (London)
✨Tip Number 1
Familiarise yourself with Azure ML and its functionalities. Since the role specifically requires experience in deploying and managing machine learning models using Azure, having hands-on experience or completing relevant online courses can give you a significant edge.
✨Tip Number 2
Network with professionals in the pensions and insurance sectors. Engaging with industry experts on platforms like LinkedIn can provide insights into the company culture at XPS Group and may even lead to referrals, which can boost your chances of landing an interview.
✨Tip Number 3
Stay updated on the latest trends in machine learning and data analytics. Being knowledgeable about recent advancements can help you during discussions in interviews, showcasing your passion and commitment to the field.
✨Tip Number 4
Prepare to discuss your previous projects in detail. Be ready to explain how you designed, built, and optimised machine learning models, as well as any challenges you faced and how you overcame them. This will demonstrate your practical experience and problem-solving skills.
We think you need these skills to ace Machine Learning Operations Engineer (London)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning operations, particularly with Azure ML. Emphasise your skills in Python, SQL, and CI/CD practices, as these are crucial for the role.
Craft a Strong Cover Letter: In your cover letter, express your enthusiasm for the role at XPS Group. Mention specific projects or experiences that demonstrate your ability to design, build, and manage machine learning models, and how you can contribute to their vision.
Showcase Your Technical Skills: Include a section in your application that details your technical skills, especially those mentioned in the job description like data wrangling, model optimisation, and familiarity with Power BI. Use examples to illustrate your proficiency.
Prepare for Potential Questions: Think about how you would explain complex machine learning concepts to non-technical stakeholders. This is important as the role requires good communication skills. Prepare examples of how you've done this in the past.
How to prepare for a job interview at XPS Group
✨Showcase Your Technical Skills
Make sure to highlight your experience with Azure ML, Python, SQL, and CI/CD practices during the interview. Be prepared to discuss specific projects where you've designed, built, or optimised machine learning models, as this will demonstrate your technical expertise.
✨Understand the Business Context
Familiarise yourself with the pensions and insurance sectors, as XPS Group operates within these industries. Being able to relate your technical skills to real-world applications in these fields will show that you understand the company's mission and can contribute effectively.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities and how you handle challenges in machine learning operations. Prepare examples of how you've dealt with model drift, data quality issues, or optimising model performance in past roles.
✨Communicate Clearly with Non-Technical Stakeholders
Since you'll need to explain complex concepts to non-technical team members, practice articulating your thoughts clearly and concisely. Use simple language and relatable analogies to ensure everyone understands your insights and recommendations.
