EEOC

Data Scientist I

EEOC

full-time

Posted on:

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

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Salary

💰 $83,000 - $110,000 per year

Job Level

JuniorMid-Level

Tech Stack

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.

Requirements

  • 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