Summer Data Science Internship — ML, Big Data, Mentorship

Notre Dame; Cincinnati (OH); Presencial; USD 40.000 - 69.000; Jornada completa

Descripción de la vacante

P&G is seeking a motivated graduate student for a 12-week Data Science internship in Cincinnati, offering hands-on experience in building scalable algorithms and collaborating with data and software teams to bring models into production. The role emphasizes mentorship and applying a range of analytic techniques across diverse business contexts.

Ideal candidates are pursuing a Master’s degree in a quantitative field with strong communication, prioritization, and curiosity about

Formación

• Pursuing a Master’s degree in a quantitative field.
• 12-week internship during summer 2027 (mid/late May–early August).
• Leadership experience in applying analytics to drive insights preferred.
• Strong written and verbal communication skills.
• Ability to balance multiple priorities.
• Comfort with diverse business scenarios and strong problem-solving attitude.

Responsabilidades

• Design and develop scalable Data Science algorithms.
• Collaborate with Data and Software Engineering teams to productionize algorithms.
• Conduct exploratory data analysis, feature engineering, and model building on large datasets.
• Provide technical coaching and mentorship to develop others.
• Develop expertise in Data Science techniques and methodologies.

Conocimientos

Communication

Leadership

Problem solving

Curiosity

Prioritization

Educación

Master's degree (Data Science, Statistics, or similar)

Herramientas

Unix/Linux

Big Data (Hadoop, Spark)

SQL

Python

R

Java/Scala

Keras/TensorFlow

Tableau/KNIME

Descripción del empleo

P&G is seeking a motivated graduate student for a 12-week Data Science internship in Cincinnati, offering hands-on experience in building scalable algorithms and collaborating with data and software teams to bring models into production. The role emphasizes mentorship and applying a range of analytic techniques across diverse business contexts.

Ideal candidates are pursuing a Master’s degree in a quantitative field with strong communication, prioritization, and curiosity about