Machine Learning Engineer

• Location: Remote (will need to come into London once a month)
• Job Type: Full-time, Permanent
• Must have the Right to Work in the UK (Cannot provide sponsorship)

Join a leading UK consulting and administration business specialising in the pensions and insurance sectors. As an ML Ops Engineer in our Pensions Advisory - Data Analytics department, you will be at the forefront of developing and deploying machine learning models that enhance our consulting capabilities and client offerings.

• Model Development: Collaborate with actuarial analysts to develop machine learning and statistical models for predicting outcomes related to pension schemes. Utilize appropriate algorithms to enhance predictions and automate decision-making processes.
• Machine Learning Operations: Design, deploy, maintain, and refine statistical and machine learning models using Azure ML. Optimize model performance and ensure smooth application operations with large-scale data handling.
• Data Management and Preprocessing: Manage the collection, cleaning, and preprocessing of large datasets. Implement data pipelines and ETL processes to ensure data quality and availability.
• Software Development: Write clean, efficient, and scalable code in Python. Implement CI/CD practices for version control, testing, and code review.
• Collaboration and Training: Work closely with various teams within the organisation to integrate data science findings into practical strategies. Provide training and support to team members on machine learning tools and analytical techniques.
• Research and Development: Stay updated with the latest trends and technologies in data science and pensions to identify opportunities for innovation.

• Essential:
  • Proven experience in designing, building, optimizing, deploying, and managing business-critical machine learning models using Azure ML in production environments.
  • Strong skills in data wrangling using Python, SQL, and ADF.
  • Proficiency in CI/CD, DevOps/MLOps, and version control systems.
  • Familiarity with data visualization and reporting tools, ideally PowerBI.
  • Excellent communication and interpersonal skills, with the ability to convey technical concepts to non-technical stakeholders.
• Desirable:
  • Experience in the pensions or similar regulated financial services industry.
  • Experience working within a multidisciplinary team.

• Competitive salary and participation in an annual discretionary bonus scheme.
• 25 days holiday plus options to buy or sell additional holiday.
• Flexible bank holidays and a comprehensive pension scheme with matching contributions.
• Healthcare cash plan and a flexible benefits scheme supporting various aspects of your life.
• Life assurance cover, extensive high street discounts, and access to digital GP services.
• Paid volunteering day and employee assistance programmes for you and your household.