Data Scientist I

EEOC

full-time

Posted on: 9/3/2025

Location: Arizona, Illinois, New York • 🇺🇸 United States

✨ AI Apply

💰 $83,000 - $110,000 per year

JuniorMid-Level

MavenPandasPythonScikit-LearnSQL

About the role

Serve as a data science team member delivering machine learning and AI solutions from start to finish.
Understand business problems, aggregate and explore data, build and validate algorithms, and quantify model value with simulations.
Deploy models, measure accuracy, drift, and performance, and participate in model validation and Model Risk Management.
Produce standard and ad hoc analytic reports and develop, test, document open-source code for data analysis and modeling.
Perform data transformations, interpret results, investigate root causes, and explore/aggregate data to uncover anomalies impacting algorithms.
End-to-end feature engineering and write production level code in a dynamic environment.
Apply various machine learning techniques; partner with Product, Engineering, Sales to identify trends, perform customer value tests, and support business development.
Explain and visualize results to non-technical audiences and support data integrity/confidentiality.

Bachelor’s Degree in Engineering, Mathematics, Statistics, Computer Science, Operational Research or related field or equivalent work experience.
A minimum of 2 years data science, engineering, mathematics, or related work/ intern/ course experience is required with Bachelor's degree or Master's degree without experience (or some internship)
Able to write Model development technical documents.
Willingness to troubleshoot system/data issues hindering the analytics environment functionality.
Experience using data visualization tools.
Able to write production level code, which is well-written and explainable.
SAS, Python, SQL or R programming training or experience.
Experience applying various machine learning techniques and understanding the key parameters that affect their performance.
Ability to effectively communicate findings from complex analyses to non-technical audiences.
Ability to communicate with various levels of employees within the department and proven technical and analytical skills.
Ability and adaptability to work on multiple projects concurrently, manipulate large data sets and produce business-relevant results.
Background and drug screen