ML Operations Engineer

Proactive.IT Appointments; London; On-site; GBP 50,000 - 70,000; Full time

Job summary

Une entreprise innovante dans le domaine des logiciels actuariels recherche un Machine Learning Operations Engineer expérimenté pour rejoindre son équipe. Vous serez responsable de la conception et du déploiement de modèles ML, collaborant avec des analystes pour améliorer la prise de décision et les services clients dans le secteur des retraites. Cette opportunité est idéale pour ceux qui souhaitent faire avancer leur carrière dans un environnement dynamique et tourné vers l'avenir.

Qualifications

• Expérience en conception et gestion de modèles ML en production.
• Compétences en Python et SQL sont essentielles.
• Expérience dans l'industrie des services financiers réglementés souhaitée.

Responsibilities

• Développer des modèles de machine learning pour prédire des résultats liés aux régimes de retraite.
• Maintenir et affiner les modèles statistiques et de machine learning avec Azure ML.
• Écrire un code Python propre et efficace.

Skills

Machine Learning

Statistical Analysis

Data Wrangling

Python

SQL

Azure ML

DevOps/MLOps

Data Quality

Tools

Azure Data Factory (ADF)

Power BI

Job description

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We are looking for an experienced Machine Learning Operations Engineer (ML Ops Engineer) to join our growing team, which has been awarded Actuarial Software of the Year.

The role involves pioneering advancements in pensions and beyond, leveraging state-of-the-art technology to extract valuable and timely insights from data. This enables consultants to better advise Trustees and Corporate clients on a wide range of actuarial-related areas.

1. Collaborate 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 suitable algorithms to enhance predictions, automate decision-making, and improve client offerings.
2. Design, deploy, maintain, and refine statistical and machine learning models using Azure ML. Optimize model performance and computational efficiency. Ensure applications run smoothly, handle large-scale data efficiently, and monitor model drift, data quality, and schedule retraining pipelines.
3. Collect, clean, and preprocess large datasets to facilitate analysis and model training. Implement data pipelines and ETL processes to ensure data availability and quality.
4. Write clean, efficient, and scalable Python code. Use CI/CD practices for version control, testing, and code review.
5. Experience in designing, building, deploying, and managing business-critical machine learning models in production environments using Azure ML.
6. Experience in data wrangling with Python, SQL, and Azure Data Factory (ADF).
7. Experience with CI/CD, DevOps/MLOps, and version control.
8. Familiarity with data visualization and reporting tools, ideally Power BI.
9. Experience in the pensions or similar regulated financial services industry.

Due to high application volume, only suitable candidates will be contacted for an interview.

Proactive Appointments Limited operates as an employment agency and is an equal opportunities employer.