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# Lead Data Scientist

- **Company:** PEOPLES, THOMAS E
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Audit Trail, Information Engineering, Python (Programming Language), Machine Learning, NumPy, Cloud Platform System, Feature Engineering, Snowflake, Model Validation, Git, Pandas, Scikit Learn, Performance Monitor, Data Pipelines
- **Published:** August 24, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pelcj3iw3g

## About the Role

* Strong experience developing predictive models within financial services or another highly regulated environment.
 * Advanced Python skills (Pandas, NumPy, Scikit-learn) and strong SQL capabilities.
 * Experience working with Snowflake or similar cloud-based data platforms.
 * Strong background in exploratory data analysis, feature engineering, and model validation.
 * Experience developing production-ready machine learning solutions and monitoring frameworks.
 * Understanding of model governance, auditability, and regulatory requirements.
 * Knowledge of credit risk, forecasting, scorecards, probability models, or related analytical techniques would be highly advantageous.
 * Experience using Git and version-controlled development practices.
 * Excellent communication skills with the ability to explain complex analytical concepts to senior stakeholders.

## Description

We're looking for a Lead Data Scientist to drive the development of predictive models and analytical products in a highly regulated environment. Working closely with senior leadership, you'll take ownership of the full data science lifecycle-from data exploration and feature engineering through to model deployment, monitoring, and governance. This role is ideal for someone who enjoys solving complex business problems, building production-grade models, and delivering tangible commercial impact., * Develop and deploy predictive models to support commercial, risk, and strategic decision-making.

 * Build and maintain modelling datasets using large-scale structured data sources.
 * Lead exploratory data analysis, feature engineering, model selection, validation, and performance monitoring.
 * Design and execute forecasting, simulation, and scenario analysis to support business planning.
 * Ensure models are robust, explainable, and compliant with governance and regulatory requirements.
 * Implement reproducible, version-controlled data science workflows and best practices.
 * Collaborate with data engineering and business stakeholders to deliver scalable data products.
 * Evaluate and optimise machine learning models, balancing performance, transparency, and business value., This is an opportunity to join a highly visible, strategically important team where you'll have significant influence over the direction of analytics and data products. You'll work on complex, high-value challenges, collaborate directly with senior decision-makers, and help build capabilities that will drive long-term business growth.


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