Data Science Intern

Brunswick Corporation • Champaign, IL

2d • $18 - $26 • Hybrid

About The Position

As part of the talented team, we are seeking a curious, versatile, and hands-on Data Science Intern who is comfortable contributing to different types of projects as organizational priorities evolve. Working with teams across Brunswick’s divisions and functions, the intern will combine scientific thinking with practical engineering to turn open-ended questions into structured analyses, experiments, and working prototypes. Projects may involve product, application, operational, telemetry, or other business data, with an emphasis on understanding data quality, extracting useful information, and designing efficient approaches for collecting, processing, and using data. The ideal candidate can learn unfamiliar domains quickly, evaluate technical trade-offs, write reliable code, and clearly communicate findings, limitations, and recommendations. At Brunswick, we have passion for our work and a distinct ability to deliver.

Requirements

• Candidates must be authorized to work in the United States immediately, without the need for sponsorship, now or in the future.
• Currently enrolled in a bachelor’s or master’s program at the University of Illinois-Urbana Champaign in Data Science, Computer Science, Statistics, Engineering, Applied Mathematics, or related fields.
• Demonstrated experience using Python for data analysis, experimentation, or prototyping, including tools such as Polars and NumPy.
• Ability to write clear, modular, and testable code and to turn analytical ideas into working scripts or prototypes.
• Working knowledge of statistics, experimental design, exploratory data analysis, data visualization, and evaluating whether results preserve the information needed for a given use case.
• Ability to analyze noisy, incomplete, or high-volume real-world data and assess the quality, representativeness, and practical usefulness of results.
• Strong problem-solving skills and willingness to learn new tools, domains, and technical concepts as project needs change.
• Strong written and verbal communication skills, including the ability to explain analytical findings and technical trade-offs clearly.

Nice To Haves

• Experience analyzing time-series, sensors, telemetry, or other streaming data.
• Familiarity with sampling theory or methods, signal processing, anomaly detection, data compression, feature extraction, or edge computing.
• Experience building data-processing pipelines or prototypes using Python and SQL, with attention to data quality, reproducibility, and performance.
• Familiarity with software engineering practices such as source control, code review, testing, debugging, and modular design.
• Experience with cloud data or analytics environments such as Azure, AWS, or GCP.
• Exposure to IoT systems, data acquisition, connectivity data flows, embedded systems, or resource-constrained devices.
• Interest in connected products, digital ecosystems, manufacturing, recreational products, or applying data science across varied business domains

Responsibilities

• Contribute to a variety of data science, analytics, research, and engineering projects based on evolving product and business needs.
• Translate ambiguous questions into measurable objectives, testable hypotheses, experiments, and practical implementation plans.
• Collect, clean, join, validate, and explore data from connected products, applications, cloud platforms, and operational systems.
• Analyze structured, unstructured, time-series, telemetry, usage, and sensor data to identify patterns, anomalies, trends, and opportunities.
• Develop reusable scripts, data-processing workflows, simulations, and prototypes that move an idea from analysis toward a working technical solution.
• Design experiments to compare alternative approaches and quantify trade-offs involving data fidelity, accuracy, performance, cost, storage, bandwidth, latency, and maintainability.
• Explore efficient methods for collecting and processing high-volume or resource-intensive data, including sampling, aggregation, filtering, compression, feature extraction, or event-driven approaches.
• Apply appropriate statistical, signal-processing, analytical, or machine-learning methods while considering the constraints of the systems in which they may be used.
• Partner with product, software, engineering, operations, and business teams across multiple divisions to develop useful and achievable deliverables.
• Test, document, and communicate datasets, code, assumptions, experimental results, limitations, and recommendations so others can reproduce and extend the work.

Benefits

• Internships are designed to provide hands-on experience in a professional setting.
• Work alongside experienced professionals and get a chance to apply academic knowledge to real-world tasks.
• The work environment is supportive, collaborative, and conducive to learning.
• Interns typically work on specific projects or tasks that contribute to the organization’s goals.
• Interns will receive feedback and performance reviews throughout their assignment.
• Interns are expected to manage their own schedules, set goals, and seek feedback for their professional development.

What This Job Offers

• Job Type: Part-time
• Career Level: Intern
• Education Level: Associate degree