Machine Learning Operations Engineer – 11328SR

Proactive.IT Appointments Limited; City Of London; On-site; GBP 40,000 - 65,000; Full time

Job summary

A financial services provider in London is seeking a Machine Learning Operations Engineer for a hybrid role. This position involves developing and optimizing machine-learning models using Azure ML and collaborating with actuarial teams. Ideal candidates should have a strong background in Python, CI/CD, and experience in the financial services sector. Competitive salary and comprehensive benefits are offered.

Benefits

Competitive salary

Participation in Discretionary Bonus Scheme

Pension Plan

Life Assurance cover

Employee assistance programme

25 days holiday

Access to a qualified GP 24/7

Qualifications

• Experience in designing and managing machine-learning models using Azure ML.
• Strong skills in data wrangling with Python and SQL.
• Familiarity with CI/CD and DevOps practices.

Responsibilities

• Develop machine-learning models to predict outcomes related to pension schemes.
• Optimize model performance and maintain operational efficiency.
• Serve as a technical resource for team members and stakeholders.

Skills

Model development

Machine Learning Operations

Data Management and Preprocessing

Software Development in Python

Communication Skills

Tools

Azure ML

Python

SQL

ADF

PowerBI

Job description

Machine Learning Operations Engineer

11328SR
£40k – 65k per year

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 at their offices in London.

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 smooth application operation with large‑scale data, and implement and maintain monitoring of model drift, data‑quality alerts and scheduled re‑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, the 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 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, optimizing, 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 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 yourself 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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