Data Scientist Intern

the Voith Group•Appleton, WI

11h

About The Position

We are seeking a highly analytical, self-driven Data Scientist Intern to support the design and development of innovative data-driven solutions across our organization. The ideal candidate will have a solid foundation in statistical modeling and machine learning, with hands-on experience using Python for data analysis and model development. This role will assist in building predictive models, developing scalable data pipelines, and conducting rigorous quantitative analysis to inform strategic decisions. As a Data Scientist Intern, you will work closely with senior data scientists and cross-functional teams to explore datasets, prototype algorithms, and translate analytical findings into clear, actionable recommendations. The position is well-suited for someone who is intellectually curious, eager to learn advanced methods, and motivated to solve complex problems with data.

Requirements

Excellent verbal and written communication skills.
Excellent organizational skills and attention to detail.
Excellent time management skills with a proven ability to meet deadlines.
Ability to function well in a high-paced environment.
Familiarity with machine learning concepts, neural networks, and algorithm design.
Proficiency in Python and common data science libraries (pandas, NumPy, scikit-learn; experience with PyTorch/TensorFlow is a plus)
Strong analytical mindset with the ability to break down complex problems into structured steps.
Exposure to financial modeling, predictive analytics, or time-series forecasting is a bonus.
Ability to communicate technical results clearly and collaborate in a cross-functional environment.
Self-motivated with a strong desire to learn and contribute to impactful real-world projects.
Pursuing a Bachelor’s or Master’s Degree in Data Science, Computer Science, Statistics, Econometrics, Engineering, or a related quantitative field.

Nice To Haves

Prior internship in Data Science, Software Engineering, or Data Engineering is a plus.
Personal or academic projects demonstrating hands-on experience with Python, machine learning models, neural networks, or applied analytics are strongly preferred.

Responsibilities

Assist in developing machine learning models for forecasting, classification, optimization, and anomaly detection.
Support the construction and maintenance of scalable data structures, including feature engineering and data cleaning workflows.
Conduct exploratory data analysis and statistical evaluations to uncover patterns, trends, and opportunities for improvement.
Implement prototype algorithms in Python using libraries such as pandas, NumPy, scikit-learn, and PyTorch.
Collaborate with senior team members to evaluate model performance, tune hyperparameters, and document results.
Communicate analytical findings through clear visualizations, dashboards, and technical summaries.
Contribute to process optimization and continuous improvement initiatives across operations, finance, and engineering teams.