About the Position
We are looking for a Senior Data Scientist to contribute to a large scale balance sheet and pricing optimisation initiative within a global financial services environment. You will focus on developing production ready financial models that support mortgage pricing innovation, working with UK mortgage time series data in a cloud native setup.
About the Project
The project focuses on enhancing pricing and performance metrics for mortgage products as part of a broader balance sheet management programme. The team is building a scalable pricing optimisation process on AWS that supports data driven decision making across the business.
About the Team
You will work within a cross functional delivery team that includes Data Scientists, Data Engineers, Data Analysts, Pricing Managers, and business stakeholders. Collaboration is central to the role, with close interaction between technical specialists and pricing and finance teams to deliver end to end solutions.
Responsibilities
- Develop and implement financial and statistical models using UK mortgage time series data
- Contribute to pricing optimisation solutions deployed within the AWS ecosystem
- Collaborate with data engineering and analytics colleagues to design scalable and maintainable data pipelines
- Perform feature engineering, model training, and validation using large datasets
- Translate complex financial and pricing data into clear insights for business stakeholders
- Support production readiness through version control, testing, and documentation in a corporate environment
Requirements
- Hands on experience delivering data science solutions on AWS in a production environment
- Practical experience with segmentation, classification, and time series machine learning models focused on pricing and analytics rather than AI or large language model use cases
- Strong programming skills in Python, PySpark, and SQL for data processing and model development
- Experience using AWS services such as SageMaker Studio and AWS Glue
- Ability to read, integrate, and transform data from multiple data lakes and data warehouses including S3, Athena, and Snowflake
- Experience with code management and collaboration using GitLab in an enterprise setting
- Business exposure to mortgage or related financial products with the ability to turn analytical results into actionable insights
Nice to Have
- Experience building dashboards or visual analytics using Amazon QuickSight
- Front end exposure with React or JavaScript for lightweight data presentation
Technologies
Python, PySpark, SQL, AWS SageMaker Studio, AWS Glue, Amazon S3, Amazon Athena, Snowflake, GitLab, Amazon QuickSight, React, JavaScript