Machine Learning Operations Engineer – 11328SR6 in Bristol

Our financial services client based in London is looking to recruit a Machine Learning Operations Engineer. The position will be a Hybrid role, working from home and 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: Design, deploy, maintain and refine statistical and machine learning models using Azure ML. Optimize model performance and computational efficiency. Ensure that applications run smoothly and handle large-scale data efficiently. Implement and maintain monitoring of model drifts, data-quality alerts, and scheduled retraining 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

• Experience 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

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