Senior Data Scientist with AWS, Mortgage Pricing Platform

Bengaluru

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Project overview

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.

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.

Position overview

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.

Technology stack

Python, PySpark, SQL, AWS SageMaker Studio, AWS Glue, Amazon S3, Amazon Athena, Snowflake, GitLab, Amazon QuickSight, React, JavaScript

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

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