Clarios is looking to solve real-world challenges in manufacturing and supply chain using data-driven approaches. The company aims to leverage data science and AI to improve decision-making, forecast outcomes, and classify information based on organizational needs.
Requirements
- statistical and machine learning algorithms
- programming languages such as Python and SQL
- visualization/reporting tools such as Power BI and SAP Business Objects
- data tools and technologies
- Python’s pandas
- Snowflake SQL
- Snowpark, Azure data factory, Matillion
Responsibilities
- Collecting, cleaning, and analyzing large data sets, developing predictive models, and visualizing insights to support strategic decision-making.
- Gain hands-on experience with statistical and machine learning algorithms, programming languages such as Python and SQL, visualization/reporting tools such as Power BI and SAP Business Objects and data tools and technologies.
- Engaging with raw datasets, applying thoughtful preprocessing and feature engineering techniques to uncover actionable patterns.
- Leveraging tools like Python’s pandas, Snowflake SQL, Snowpark, Azure data factory, Matillion etc., you’ll build models that forecast outcomes or classify information based on real organizational needs.
- Collaborating by sharing your findings with your team, refining approaches in response to feedback, and contributing to brainstorming sessions that shape project direction.
- Adapting your workflow to maximize productivity and learning.
- Contributing to strategic initiatives, developed a portfolio of real-world work, and mastered both the technical and interpersonal aspects of the data science profession.
Other
- Currently enrolled as a full-time student at an accredited U.S. college or university.
- Pursuing an undergraduate degree in Data Science.
- Ability to be in the greater Milwaukee area in the summer.
- Duration: Summer 2026.
- Applicants must be authorized to work for any employer in the US without the need for sponsorship, now or in the future.
