Machine Learning Operations Engineer

Proactive.IT Appointments Limited; Greater London; Hybrid; GBP 40,000 - 60,000; Full time

Job summary

A leading financial services firm based in London is seeking a Machine Learning Operations Engineer. The role involves developing and optimising machine learning models using Azure ML and working collaboratively with actuarial analysts. The ideal candidate should excel in Python programming and have experience in data management and CI/CD practices. Competitive salary and comprehensive benefits are offered for the right candidate. Join this hybrid position to make a significant impact in the financial services sector.

Benefits

Competitive salary

Discretionary Bonus Scheme

Pension Plan

Life Assurance

Employee Assistance Programme

25 days holiday

24/7 access to a GP

Flexible Benefits Scheme

Qualifications

• Experience designing and managing machine learning models in production.
• Proficient in Python and SQL for data wrangling.
• Strong interpersonal skills to communicate with non-technical stakeholders.

Responsibilities

• Develop machine learning models with actuarial analysts.
• Design and deploy models using Azure ML.
• Collect and preprocess datasets for training.
• Write scalable code in Python.

Skills

Machine Learning Model Development

Python Programming

Data Management

Azure ML

CI/CD Practices

Communication Skills

Tools

Azure ML

PowerBI

SQL

Job description

11328SR6
£40k – 60k per year

Machine Learning Operations Engineer

Our financial services client based in London is looking to recruit a Machine Learning Operations Engineer ASAP. The position will be a Hybrid role be working from home and their offices in London. To be considered for the role you must have the following essential skills & experience:

Key Skills & Experience

• 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 the company 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 the company.

Technical Skills required

• 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

Benefits

• We offer an attractive reward package; typical benefits can include:
• Competitive salary
• Participation in Discretionary Bonus Scheme
• A set of core benefits including Pension Plan, Life Assurance cover and employee assistance programme, 25 days holiday and access to a qualified, practising GP 24 hours a day/365 days a year
• 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

Due to the volume of applications received for positions, it will not be possible to respond to all applications and only applicants who are considered suitable for interview will be contacted.

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