Summer Internship Opportunity

Our own Ethan Zell (read his story here) reached out to share that the company where he did his internship, Mined XAI, is hiring an intern again this summer. Here is a cut/paste of the position description:

Summer Internship

Mined XAI [“mind’s eye”] is machine learning and data analytics company based in Dayton, Ohio.  Our explainable AI solutions uses deep topological modeling platform structures to integrate and synthesize multi-domain knowledge for direct human interaction. We have an exciting opportunity for a highly skilled intern to join an innovative and dynamic group

Internship

Will be for 8 weeks in summer of 2023. Pay is $20/hour with 40 hours max a week. Interns will be developing architecture for Topologial Data Analysis in the finance/economics area. Interns will present findings every week with a final presentation at the end of the internship.

About You

Learn on how to transform data into an actionable outcome utilizing deep topological modeling. Must be highly analytical and have the proven ability to develop and reverse complex engineering solutions. Critical thinking, advanced problem-solving and collaborative skills are core behaviors that we seek.

Skills & Experience

  • Experience using statistical computer languages and packages (Python, SLQ, Pandas, Numpy, etc.) to manipulate data and draw insights from large data sets
  • Experience in data extraction, maintenance, and statistical transformations
  • Experience working with and creating data architectures
  • Excellent written and verbal communication skills
  • Ability to create interactive visualization dashboards is desired.
  • Working on a Bachelor’s, Master’s or PhD in a related field.
  • Experience in working with finance/economics data is preferred but not required.
  • Must be a US citizen or permanent resident.

Other Requirements &Travel

  • Preferred ability to be local in Dayton area but will consider remote interns
  • Can offer a housing allowance
  • Remote workers will travel to Dayton at beginning and end of internship

By Karen E Smith

Professor of Mathematics Associate Chair for Gradate Studies