Remote Data Analytics Fall Internship Jobs in Chicago, IL

The Data Scientist is responsible for delivering data-driven insights and analytical solutions that support business decision-making. This role partners closely with business stakeholders, data engineering, and development teams to analyze complex datasets, build visualizations, and develop predictive models. The ideal candidate combines strong analytical skills with business acumen and effective communication in an Agile environment.

Required:

• Master's degree in Data Science, Data Analytics, Computer Science, or related field
• 3-5 years of experience in data analytics or data science roles
• Strong proficiency in SQL, Python, and R
• Experience with Power BI, Tableau, or similar visualization tools, including data modeling and DAX
• Strong analytical and problem-solving skills with attention to detail
• Experience gathering and documenting business requirements
• Familiarity with Agile methodologies and Azure DevOps
• Excellent communication, interpersonal, and stakeholder management skills
• Understanding of statistical methods and probability theory

Preferred: 

• Experience with machine learning frameworks such as scikit-learn, TensorFlow, or Keras
• Experience with Salesforce data and reporting
• Experience in business services or manufacturing industries
• Familiarity with NLP or deep learning techniques

What you'll experience working for ULS 

UL Solutions has been pioneering change since 1894 and we're still leading the way. From day one, we've blazed a trail protecting the planet and everyone on it. Our teams have influenced billions of products, plus services, software offerings and more. We break things, burn things and blow things up. All in the name of safety science. 

That's where you come in - because none of it could happen without you. It takes passion to protect people, problem-solving to safeguard personal data and conviction to make the world a more sustainable place. It takes bold ideas and brilliant minds to build a better world for future generations across the globe.  

This is more than a job. It's a calling. A passion to use our expertise and play our part in creating a more secure, sustainable world today - and tomorrow. As a member of our safety science community, you'll use your ideas, your energy and your ambition to innovate, challenge and ultimately, help create a safer world. 

Everyone here is unique. But we're also a global community, working together to help create a safer world. Join UL Solutions and you can connect with the brightest minds in the business, all bringing their distinct perspectives and diverse backgrounds together to deliver real change. 

Empowering our customers to keep the world safe means thinking ahead. It means investing in training and empowering our people to learn and innovate. At UL Solutions, we help build a better future - one where everyone benefits. 

Join UL Solutions to be at the center of safety. To learn more about us and the work we do, visitUL.com 

Total Rewards: We understand compensation is an important factor as you consider the next step in your career. The estimated salary range for this position is $80,000 to $120,000 and is based on multiple factors, including job-related knowledge/skills, experience, geographical location, as well as other factors. This position is eligible for annual bonus compensation with a target payout of 10% of the base salary. This position also provides health benefits such as medical, dental and vision; wellness benefits such as mental and financial health; and retirement savings (401K) commensurate with the standard rewards offered in each individual location or country. We also provide full-time employees with paid time off including vacation (15 days), holiday including floating holidays (12 days) and sick time off (72 hours).

Accepting applications until 12/15/2026

#LI-SG2

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• Process, cleanse, and verify the integrity, quality, and reliability of data used for analysis, reporting, and predictive modeling.
• Perform ad-hoc and recurring analyses, presenting results and insights in a clear, concise manner to support business decision-making.
• Analyze large, complex datasets to extract meaningful insights, selecting appropriate statistical, analytical, and machine learning techniques based on the problem context.
• Select relevant features and build, evaluate, and optimize classification and predictive models using machine learning techniques.
• Apply data mining and advanced analytical methods to identify trends, patterns, and relationships within structured and unstructured data.
• Extend and enrich customer and business datasets using third-party data sources when required to improve analytical outcomes.
• Enhance data collection and preparation procedures to ensure relevant, high-quality inputs for analytic and machine learning systems.
• Use data modeling and evaluation strategies to identify patterns and accurately predict unseen or future instances.
• Collaborate with business and technical stakeholders to align analytical solutions with business objectives.
• Adhere to the Underwriters Laboratories Code of Conduct and follow all physical and digital security, data governance, and compliance practices.Collaborate with business stakeholders to gather, analyze, and document requirements, translating needs into BRDs, user stories, and functional specifications.
• Analyze large, complex datasets using statistical and analytical techniques to identify trends, patterns, and actionable insights.
• Build and maintain dashboards, reports, and data visualizations using Power BI, Tableau, or similar tools.
• Apply statistical methods and basic machine learning models to support forecasting, prediction, and business decision-making.
• Perform ad-hoc and recurring analyses to support both operational reporting and strategic initiatives.
• Process, cleanse, validate, and maintain data accuracy and integrity across analytical datasets.
• Enhance data collection processes and integrate third-party data sources to improve analytical coverage and model performance.
• Communicate analytical findings and recommendations clearly to both technical and non-technical audiences.
• Partner with development teams using Azure DevOps to manage work items, track progress, and ensure timely delivery.
• Support data science and analytics initiatives using SQL, Python, R, and Excel.
• Collaborate with data engineering teams to support analytics pipelines and data lake initiatives.