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# Senior Data Scientist

- **Company:** Dormont Manufacturing Co
- **Location:** Bexhill, UK
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Microsoft Azure, Github, Python (Programming Language), Machine Learning, Azure Machine Learning, SQL Databases, Git, Machine Learning Operations
- **Published:** September 10, 2026
- **Apply:** https://www.collegerecruiter.com/job/2840590242-senior-data-scientist

## About the Role

* Track record of building, validating, and maintaining pricing models (e.g. GLMs, GAMs, tree-based models).
 * Experience in developing new pricing initiatives to make use of new models or data items, challenging the established approaches.
 * Experience in liaising with multiple stakeholders to effectively frame problems and building solutions with effective commercial outcomes.
 * Proficiency in Python, SQL, Azure ML, Git, Azure Cloud Services
 * Strong communication skills.
 * Ability to work cross-functionally with Data Engineers, Data Scientists and Pricing Analysts.
 * Keen interest in emerging ML techniques and their commercial value.

Desirable

 * Insurance industry experience.
 * ML Ops experience.
 * GitHub as a code collaboration tool.
 * Experience in line management., * Highly technically competent mixed with broader business understanding.
 * Natural problem solver who loves building creative solutions to complex real-world challenges.
 * Ability to work independently or collaboratively as part of a team to deliver solutions to a well-defined set of requirements.
 * Dynamic, flexible and delivery-focused work ethic required to adapt to a fast-paced environment.

## Description

* Building ML and GLM models for deployment into live pricing, including feature engineering and trialling new modelling approaches.
 * Build a deep understanding of our price optimisation lifetime value function and contribute to its development.
 * Develop new experimental pricing approaches, exploring new optimisation approaches, model structures, and automated learning.
 * Work hand in hand with ML ops and engineering functions to deploy and test new approaches.


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