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# Data Scientist

- **Company:** Environmental Systems Research Institute, Inc.
- **Location:** St. Louis, MO, United States
- **Experience:** Starter
- **Salary:** $70,304.0 - $110,240.0
- **Contract:** Permanent contract
- **Skills:** Big Data, Data Mining, Data Systems, Data Visualization, Python (Programming Language), Machine Learning, Rapid Prototyping Process, Data Streaming, Esri GIS (Software), Feature Engineering, Large Language Models, Multi-Agent Systems, Deep Learning, Information Technology
- **Published:** September 2, 2026
- **Apply:** https://www.esri.com/careers/5173232007

## About the Role

* 1+ years of professional experience in a similar position, supporting similar responsibilities
 * Professional experience with practical machine learning experience or relevant academic/lab work
 * Hands-on relevant experience in generative AI, large language models, and/or agentic systems
 * Fundamental understanding of mathematical and machine learning concepts
 * Applied statistics experience
 * Experience developing machine learning solutions, preferably in Python
 * Ability to produce compelling data visualizations to convey results
 * Strong communication skills, including the ability to explain technical concepts to non-technical audiences
 * US citizenship and willingness and ability to maintain a US Security Clearance
 * Bachelor's degree in mathematics, statistics, computer science, physics, or a STEM related field

Recommended Qualifications

 * Experience with spatial and GIS concepts, preferably using Esri software
 * Master's degree in mathematics, statistics, computer science, physics, or a STEM related field

#LI-AN1

## Description

* Consult closely with customers to understand their needs
 * Develop and pitch data science solutions by mapping business problems to machine learning or other advanced analytics approaches
 * Build high-quality analytics systems that solve our customers' business problems using techniques from data mining, statistics, and machine learning
 * Write clean, collaborative, and version-controlled code to process big data and streaming data from a variety of sources and types
 * Perform feature engineering, model selection, and hyperparameter optimization to yield high predictive accuracy and deploy the model to production in a cloud, on-premises, or hybrid environment
 * Implement best practices and patterns for geospatial machine learning and develop reusable technical components for demonstrations and rapid prototyping
 * Keep up to date with the latest technology trends in machine and deep learning and incorporate them in project delivery


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