Data Scientist Intern - Columbus, OH

American Electric Power•Columbus, OH

About The Position

American Electric Power is seeking highly motivated Data Scientist Interns to gain hands-on experience in data analysis, modeling, and interpretation in a dynamic environment. The role is suited to someone with a strong analytical mindset and a passion for data-driven decision-making. Interns assist with collecting, cleaning, and analyzing large datasets; developing statistical models and machine learning algorithms; collaborating with cross-functional teams on data-driven business solutions; presenting findings to stakeholders; and documenting processes and methodologies. The position is located in Columbus, Ohio. The posting ends November 13, 2026, and closes the day before that date. The stated physical demand level is sedentary, involving mostly sitting with occasional walking or standing and exerting up to 10 pounds of force occasionally.

Requirements

  • Currently pursuing a degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
  • Proficiency in Python or R.
  • Familiarity with data manipulation libraries such as Pandas and NumPy, and machine learning frameworks such as Scikit-learn and TensorFlow.
  • Strong understanding of statistical concepts and data analysis techniques.
  • Excellent communication skills and ability to work collaboratively in a team environment.

Nice To Haves

  • Experience with SQL for database management.
  • Knowledge of data visualization tools such as Tableau or Power BI.
  • Previous internship or project experience in data analysis or related fields.

Responsibilities

  • Assist in collecting, cleaning, and analyzing large datasets to extract meaningful insights.
  • Develop and implement statistical models and machine learning algorithms.
  • Collaborate with cross-functional teams to identify data-driven solutions to business challenges.
  • Visualize data and present findings to stakeholders using tools such as Tableau or Power BI.
  • Document processes and methodologies for future reference.
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