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Data Science New Grad Jobs in Chicago, IL (NOW HIRING)

Numerator

Director, Data Science

Chicago, IL · On-site

As Director of Data Science , you will lead the team responsible for Numerator's consumer panel ... new statistical and machine learning methods where they strengthen the platform * Partner with ...

Numerator

Director, Data Science

Chicago, IL

As Director of Data Science , you will lead the team responsible for Numerator's consumer panel ... new statistical and machine learning methods where they strengthen the platform * Partner with ...

ZS

Advanced Data Science Manager

Evanston, IL · On-site

$225K - $240K/yr

Develop/sell new business opportunities * Direct multiple projects simultaneously, honing analytic and project management skills; * Play a key role in development of data science capabilities and ...

Reyes Holdings

Data Scientist

Rosemont, IL

... Data Science specialization * Understanding of data structures, algorithms, and distributed computing, both for data and optimization * Familiarity to AI, Machine Learning NLP, including new and ...

Reyes Holdings

Data Scientist

Rosemont, IL

... Data Science specialization * Understanding of data structures, algorithms, and distributed computing, both for data and optimization * Familiarity to AI, Machine Learning NLP, including new and ...

Sonsoft Inc

Data Science/Analytics

Chicago, IL

Define new business metrics as required and build measurement systems as needed * Enjoy designing, develop and deploy state of the art, data-driven predictive models * Adept in quick starting ...

Sonsoft Inc

Data Science Analytics

Chicago, IL

Define new business metrics as required and build measurement systems as needed * Enjoy designing, develop and deploy state of the art, data-driven predictive models * Adept in quick starting ...

Ulta Beauty, Inc.

Data Scientist

Bolingbrook, IL · On-site

$102K - $130K/yr

... the New York City Fair Chance Act. Qualifications: ESSENTIALS FOR SUCCESS: * 2+ years of professional experience in data science, machine learning, or analytics functions, with a track record of ...

Ulta Beauty

Data Scientist

Bolingbrook, IL · On-site

$102K - $130K/yr

From ongoing investment in new and emerging technologies to a career of self-determination. At Ulta ... Design and develop data science and machine learning models to optimize operational tactics ...

Ulta Beauty, Inc.

Data Scientist

Bolingbrook, IL · On-site

$102K - $130K/yr

... the New York City Fair Chance Act. Qualifications: ESSENTIALS FOR SUCCESS: * 2+ years of professional experience in data science, machine learning, or analytics functions, with a track record of ...

Reyes Holdings

Data Scientist

Rosemont, IL · On-site

$99K - $124K/yr

... Data Science specialization * Understanding of data structures, algorithms, and distributed computing, both for data and optimization * Familiarity to AI, Machine Learning NLP, including new and ...

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All JobsData Science New Grad JobsData Science New Grad Jobs in Chicago, IL

Data Science New Grad information

See Chicago, IL salary details

$38.6K

$126.4K

$202.4K

How much do data science new grad jobs pay per year?

As of Sep 4, 2026, the average yearly pay for data science new grad in Chicago, IL is $126,438.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $140,100.00 per year, depending on experience, location, and employer.

What is a data science new grad?

Data Science New Grad roles are entry-level positions designed for recent graduates who have completed a degree in data science, computer science, statistics, or a related field. These roles typically involve working with data to analyze trends, build predictive models, and support business decision-making. New grads are expected to have foundational knowledge in programming, statistics, and machine learning, but are not required to have extensive work experience. These roles often offer mentorship and training to help new professionals grow their technical and analytical skills. Companies hire Data Science New Grads to bring fresh perspectives and to develop future data science talent.

What are the key skills and qualifications needed to thrive as a data science new grad?

To thrive as a Data Science New Grad, you need a strong foundation in statistics, programming (typically Python or R), and data analysis, often supported by a degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks (such as TensorFlow or scikit-learn), data visualization tools, and SQL databases is highly valued. Strong problem-solving abilities, communication skills, and curiosity help new grads stand out when interpreting data and presenting insights. These competencies are crucial for transforming complex data into actionable business solutions and collaborating effectively within multidisciplinary teams.

What types of projects can a data science new grad expect to work on during their first year?

As a Data Science New Grad, you can expect to work on a variety of projects such as cleaning and preprocessing data, developing predictive models, and assisting with data visualization and reporting. You may also collaborate closely with product managers, engineers, and senior data scientists to translate business problems into analytical solutions. Early projects often focus on building foundational skills and understanding the company’s data infrastructure, while gradually increasing in complexity as you gain experience. This hands-on exposure is designed to help you grow technically and understand how data science supports organizational goals.

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Data Science New Grad jobs near you
Infographic showing various Data Science New Grad job openings in Chicago, IL as of August 2026, with employment types broken down into 4% Internship, 76% Full Time, 11% Part Time, 2% Temporary, and 7% Contract. Highlights an 85% In-person, 6% Hybrid, and 9% Remote job distribution, with an average salary of $126,438 per year, or $60.8 per hour.

Director, Data Science

Numerator

Chicago, IL • On-site

Full-time

Re-posted 27 days ago

Key responsibilities

  • Lead, coach, and develop a team of data scientists and data science managers focused on consumer behavior, panel methodology, and measurement science

  • Own the quality, currency, and representativeness of the panel signal end to end, including advancing methods for attribution, compliance, anomaly detection, and panelist demographics

  • Partner with cross-functional teams to translate scientific advances into scalable product capabilities and communicate complex technical concepts clearly

Job description

At Numerator, understanding consumers begins with one of the industry’s richest and most comprehensive views of real-world purchasing behavior. For more than a decade, Numerator has pioneered and led the science of representing consumer purchasing behavior across retailers, channels, brands, categories, demographics, and geographies.  

As Director of Data Science, you will lead the team responsible for Numerator's consumer panel — the quality, currency, and representativeness of the signal at the heart of our data. Your team owns how well the panel reflects the population, how we understand where it doesn't, and the methodologies that keep it accurate, current, and trustworthy. You'll partner closely with Market Science, Engineering, Product, and GTM to turn that signal into products and estimates clients rely on.

We’re looking for a leader who enjoys challenging assumptions, translating client needs into innovation, and developing exceptional data scientists. You should be equally comfortable debating statistical methodology, mentoring a team, partnering with Engineering and Product, and explaining complex concepts in language that drives better business decisions.

What You'll Do:

Team Leadership:

  • Lead, coach, and develop a team of data scientists and data science managers focused on consumer behavior, panel methodology, and measurement science

  • Grow the leaders on your team — developing managers, not only individual contributors — and raise the technical bar through mentorship, methodology reviews, and adoption of modern statistical approaches

  • Foster a culture of scientific curiosity, rigor, and peer review, where decisions are grounded in evidence and healthy debate rather than precedent or intuition

  • Build an AI-native data science team by thoughtfully integrating AI into research, experimentation, software development, and scientific workflows — helping scientists move faster while maintaining rigorous standards

  • Maintain regular engagement with clients to deepen understanding of their challenges, build confidence in Numerator's methodology, and keep client needs central to the team's priorities

Consumer Science & Methodology 

  • Own the quality, currency, and representativeness of the panel signal end to end — advancing methods for attribution completeness, compliance, anomaly detection, and keeping panelist demographics current

  • Characterize how the panel represents — and mis-represents — the population, treating that as a first-class, proactive modeling discipline rather than reactive data cleanup

  • Steward the panel as a living asset, partnering across the business on recruitment, engagement, and panel health, and turning evidence of where the panel is thin into targeted, prioritized investment

  • Design methodologies that improve the stability, consistency, explainability, and scientific defensibility of Numerator's consumer data

Statistical Innovation

  • Challenge existing approaches through first-principles thinking, and research, prototype, and productionize new statistical and machine learning methods where they strengthen the platform

  • Partner with Market Science to advance the statistical foundations of Numerator's products

Cross-Functional Leadership

  • Partner closely with Market Science, Engineering, Product, and GTM — contributing the deep panel understanding that powers the broader measurement system, and translating scientific advances into scalable product capabilities

  • Communicate complex technical concepts clearly to technical and non-technical audiences

  • Balance scientific rigor with practical business impact and client value

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