Machine Learning Engineer

In Technology Group; United Kingdom; Hybrid; GBP 45,000 - 60,000; Full time

Job summary

A leading technology group is seeking a Machine Learning Engineer in London to join their expanding Data Analytics business. In this role, you will develop and manage machine learning models using Azure ML, ensuring optimal performance while collaborating with multidisciplinary teams. With a focus on innovation and data management, this position offers flexibility in work arrangements, alongside competitive salary and benefits.

Benefits

Annual discretionary bonus scheme

25 days holiday plus options to buy or sell holiday

Flexible bank holidays and benefits scheme

Life assurance (4x salary)

Discount offers and employee assistance

Qualifications

• Experience in ML model deployment using Azure ML.
• Proficient in Python, SQL, and version control with CI/CD.
• Good communication skills for explaining technical concepts.

Responsibilities

• Develop machine learning models to predict pension outcomes.
• Maintain and optimize models using Azure ML.
• Collaborate with teams to integrate data science insights.

Skills

Python

SQL

Data Management

Machine Learning

CI/CD

Communication

Tools

Azure ML

Power BI

Job description

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Job Title: Machine Learning Engineer

Location: London (1 day per week onsite) - Flexible

Salary: £45,000 DOE + Benefits

Our Data Analytics business continues to grow, and we are now looking for an experienced and technical Machine Learning (ML) Engineer to join one of our offices with hybrid or remote UK working. This is an exciting role, suitable for someone with previous experience in 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.

About the Company

A FTSE 250 company, they combine expertise and insight with advanced technology and analytics to address the needs of over 1,400 schemes and their sponsoring employers. They undertake administration for over one million members and provide advisory services to schemes and corporate sponsors, including 88 with assets over £1bn. They also support insurance companies in the life and bulk annuities sector.

The Team

The client is a multidisciplinary team of actuaries, data scientists, and developers. Their role is to pioneer advancements in pensions and beyond, leveraging state-of-the-art technology to extract valuable insights from data, enabling better advice to trustees and corporate clients.

The Role

As a Machine Learning Engineer, you will:

• Model Development: Collaborate with actuarial analysts to develop machine learning and statistical models to predict pension outcomes such as life expectancy, default risk, or investment returns. Identify suitable algorithms to enhance predictions and automate decision-making.
• Machine Learning Operations: Design, deploy, maintain, and refine models using Azure ML. Optimize performance, ensure applications run smoothly, and handle large datasets efficiently. Implement monitoring for model drift and data quality.
• Data Management and Preprocessing: Collect, clean, and preprocess large datasets. Develop data pipelines and ETL processes to ensure data quality and availability.
• Software Development: Write clean, scalable Python code, utilizing CI/CD practices for version control, testing, and review.
• Collaboration: Work with actuarial teams to integrate data science insights into practical strategies.
• Innovation & Support: Stay updated on new trends, provide training, and explain technical concepts to non-technical stakeholders.

Your Profile

Essential Criteria

• Experience in designing, building, deploying, and managing ML models with Azure ML in production.
• Proficiency in Python, SQL, and data wrangling tools like ADF.
• Experience with CI/CD, DevOps/MLOps, and version control.
• Familiarity with Power BI or similar visualization tools.
• Good communication skills, able to convey technical concepts clearly.
• Experience in pensions or regulated financial services is highly desirable.
• Experience working in multidisciplinary teams is beneficial.

Benefits

• Participation in annual discretionary bonus scheme
• 25 days holiday plus options to buy or sell holiday
• Flexible bank holidays and benefits scheme supporting health, wellbeing, and lifestyle
• Life assurance (4x salary)
• Discount offers, employee assistance, digital GP, volunteering days, staff referral scheme