Machine Learning Engineer

In Technology Group; London; Hybrid; GBP 50,000 - 75,000; Full time

Job summary

A leading financial services firm is seeking a Machine Learning Engineer to enhance their data analytics capabilities. The role involves developing business-critical models using Azure ML and collaborating with multidisciplinary teams to provide actionable insights in pensions. Candidates should possess strong technical skills in Python, SQL, and machine learning, along with experience in production environments.

Benefits

Annual discretionary bonus scheme

25 days holiday with flexibility

Flexible bank holidays

Life assurance cover

Digital GP service access

Qualifications

• Experience in designing and deploying machine learning models in production environments.
• Familiarity with CI/CD practices and data visualization tools like Power BI.

Responsibilities

• Develop machine learning models to predict outcomes related to pension schemes.
• Implement and maintain data pipelines and model monitoring processes.
• Work collaboratively with actuarial analysts on data science findings.

Skills

Python

SQL

Machine Learning

Azure ML

CI/CD

Data Management

Data Visualization

Job description

This range is provided by In Technology Group. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

Direct message the job poster from In Technology Group

Head of Data, BI, and AI @ In Technology Group.

Job Title: Machine Learning Engineer

Our Data Analytics business continues to grow and we are now looking for an experienced and technical Machine Learning (ML) 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 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 Phyton, SQL, CI/CD and familiar with Power BI.

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 on an ongoing and project basis. We undertake 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.

The Team

The client 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 Engineer 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 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.

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 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.

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

• Participation in annual discretionary Bonus Scheme
• 25 days holiday plus flexibility to buy or sell holiday
• Flexible Bank holidays
• 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
• 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

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Analyst and Information Technology

• Industries

  Financial Services, Insurance, and IT Services and IT Consulting

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