Senior Data Scientist

Summary: The Senior Data Scientist role involves bridging the gap between machine learning and software engineering within a financial services context. The position requires collaboration across Data Science and DevOps to deploy scalable AI/ML solutions. The candidate will be responsible for the full ML lifecycle, including model deployment and monitoring. This is a hybrid role based in Stratford, London, with a contract length of 6 months.

Key Responsibilities:

• Collaborate across Data Science and DevOps to turn experimental ML models into deployed applications.
• Package and deploy ML models (including Hugging Face Transformers) as microservices on AWS.
• Build, train, and evaluate models using AWS tools like SageMaker, Bedrock, Glue, Athena, and Redshift.
• Develop secure APIs with Apigee and build automation pipelines using Jenkins, Maven, and more.
• Support the full ML lifecycle including monitoring, governance, and reproducibility.

Key Skills:

• Degree (or equivalent experience) in Computer Science, Data Science, Mathematics, or a technical field.
• Proficiency in Python (or R), with hands-on experience in ML and statistical modeling.
• End-to-end experience with MLOps, from experimentation to deployment and monitoring.
• Strong grasp of ethical AI practices: model explainability, transparency, bias mitigation.
• Hands-on with AWS services (SageMaker, Glue, Redshift, Bedrock, Lambda, Fargate).
• Skilled in deploying and hosting microservices/APIs with Flask or FastAPI.
• Proficient in SQL, Git, Jupyter/RStudio, and CI/CD integrations.
• Excellent communication skills and ability to engage with non-technical stakeholders.
• Strong problem-solving ability and a product-first mindset.
• Enthusiastic about learning, adapting to new tools, and collaborating in a dynamic environment.

Salary (Rate): £500

City: London

Country: United Kingdom

Working Arrangements: hybrid

IR35 Status: inside IR35

Seniority Level: Senior

Industry: IT