Hybrid AI/ML Engineer — Cybersecurity Data Scientist

UnitedHealth Group

Eden Prairie (MN)

Hybrid

USD 77,000 - 138,000

Full time

12 days ago
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Benefits offered by this job

Comprehensive benefits package
Equity stock purchase
401k contribution

Job summary

UnitedHealth Group seeks an Associate AI/ML Engineer in Eden Prairie, MN to join the ESRO Cyber AI team. You will help build data science models and AI solutions that strengthen cybersecurity across a distributed environment.

The role offers hybrid-remote work from Eden Prairie and requires hands-on Python/Java development, ML/AI experience, and data engineering skills within a large organization.

Qualifications

  • Bachelor's degree in CS/IT/engineering.
  • 1+ years delivering ML/AI solutions or models.
  • 1+ years data engineering concepts and command-line coding.
  • 1+ years software development with Python or Java.
  • 6+ months GenAI experience.

Responsibilities

  • Produce meaningful data science models, ML/AI solutions impacting cybersecurity.
  • Collect, clean, process, and analyze enterprise cybersecurity data.
  • Develop ML/AI models within an operational CICD pipeline.
  • Work with source data teams to understand security and processes through data.
  • Stay current with big data, data science, ML and AI technologies.
  • Learn and adapt to new techniques, languages, and technologies.
  • Design, develop, and deploy AI-powered solutions with responsible AI focus.

Skills

Statistical modeling
Data analysis
GenAI experience

Education

Bachelor's degree in CS/IT/engineering

Tools

Python
Java
PySpark
Databricks
Azure OpenAI Studio
AWS Neptune
SQL
Unix
SAS
R

Job description

UnitedHealth Group seeks an Associate AI/ML Engineer in Eden Prairie, MN to join the ESRO Cyber AI team. You will help build data science models and AI solutions that strengthen cybersecurity across a distributed environment.

The role offers hybrid-remote work from Eden Prairie and requires hands-on Python/Java development, ML/AI experience, and data engineering skills within a large organization.

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