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IBM
·
September 7, 2026
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Cost & Asset Optimization - Data Science Analyst Intern 2027

Poughkeepsie, NY
Internship
Hybrid
$67K/yr - $122K/yr
Intern
IBM is seeking a Data Science Analyst Intern to support its Infrastructure product portfolio and Cost & Asset Optimization team. The role involves collaborating with cross-functional teams, analyzing competitors and market trends, and improving processes through automation and AI tools.

Responsibilities

  • Collaborate with cross-functional teams (product management, supply chain, procurement, development, engineering and finance)
  • Analyze competitors, market trends and industry standards
  • Optimize and improve process through use of automation and AI tools

Qualification

Required

  • High School Diploma/GED
  • Bachelor's Degree in Data Science/IT/Computer Science/Engineering
  • Exposure to agile practices and design thinking
  • Strong written and verbal communication skills
  • Problem solving and business analysis skills
  • Ability to work three days from the office
  • Ability to work without a need for current or future visa sponsorship

Preferred

  • Bachelor's Degree
  • Exposure to Cloud & Technology, Technical expertise
  • Ability to communicate with stakeholders
  • Exposure to process optimization leveraging AI tools

Benefits

  • Hybrid work arrangement
  • Supplemental 1 employees may be eligible for up to 8 paid holidays
  • Supplemental 1 employees may be eligible for a minimum of 56 hours paid sick time
  • The IBM Employee Stock Purchase Plan
  • Paid family medical leave for eligible employees where required by applicable law
  • Disability benefits for eligible employees where required by applicable law
  • Opportunities to learn and develop yourself and your career
  • Continuous trust and support in an environment where everyone can thrive
IBM provides technology and consulting, including software, infrastructure systems, and cloud-based solutions.
Glassdoor
3.9
Founded in 1911
Armonk, New York, USA
10001+ employees
http://www.ibm.com
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