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# AI Data Scientist

- **Company:** Edward D. Jones & Co., L.P.
- **Location:** St. Louis, MO, United States
- **Experience:** Expert
- **Salary:** $165,000.0 - $205,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Microsoft Azure, Continuous Integration, Information Engineering, Python (Programming Language), Machine Learning, Natural Language Processing, SQL Databases, Feature Engineering, Delivery Pipeline, Large Language Models, Deep Learning, Git, Pandas, Scikit Learn, Kubernetes, Machine Learning Operations, Software Version Control, Data Pipelines, Docker
- **Published:** October 14, 2026
- **Apply:** https://find.jobs/jobs-near-me/apply/ats-redirect/?id=3019025846-2

## About the Role

* Machine learning algorithms (supervised, unsupervised, ensemble methods)
 * Deep learning frameworks (Tensor
 * Flow, Py
 * Torch)
 * Natural language processing and LLMs
 * Python programming (Pandas, Num
 * Py, Scikit-learn)
 * Model deployment and MLOps (Docker, Kubernetes, CI/CD)
 * Cloud platforms (AWS, Azure, or GCP)
 * Data engineering for ML (SQL, data pipelines)
 * Model governance, monitoring, and explainability
 * Time-series and risk modeling for financial data
 * Version control and collaborative development (Git)

## Description

Edward Jones is seeking a Senior AI Scientist to design, build, and deploy advanced AI/ML solutions that power investment advice, risk modeling, and client personalization across our finance and insurance platforms. You will lead end to end model development, from data exploration and feature engineering to experimentation, validation, and productionization in partnership with engineering and product teams. Responsibilities include developing scalable ML pipelines, applying NLP and deep learning to financial data, ensuring model governance and compliance, and mentoring junior scientists in a collaborative, client first culture., * Design and develop advanced AI/ML models for investment advice, risk modeling, and client personalization

 * Lead end-to-end ML lifecycle including data exploration, feature engineering, training, and evaluation
 * Build and maintain scalable ML pipelines and deployment workflows with engineering teams
 * Apply NLP and deep learning techniques to structured and unstructured financial data
 * Ensure model governance, documentation, fairness, and regulatory compliance in a finance context
 * Collaborate with product and business stakeholders to translate client needs into AI solutions
 * Monitor, validate, and improve model performance in production environments
 * Mentor and provide technical guidance to junior data scientists and analysts
 * Contribute to AI strategy, tooling, and best practices across the organization