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Data Science Degree Jobs in Illinois (NOW HIRING)

Data Engineer

Villa Park, IL · On-site

$113.80K - $136.60K/yr

... of Science degree in Information Systems, Computer Science, Statistics, Data Science or other ... related field Preferred - Relevant certifications in cloud, data engineering, or analytics platform ...

Senior Manager, Data Science

Chicago, IL · On-site +1

$122.40K - $228K/yr

Data Analytics & Reporting This is ideally a hybrid role but open to remote Role Overview We are ... Advanced degree (PhD preferred) in Computer Science, Engineering, Statistics, Mathematics, Physics ...

Requires a Master's degree or foreign equivalent in Business Analysis, Data Science, Applied Computer Science, Mathematics or related field and 4 years of experience as a Data Analyst, Business ...

Requires a Master's degree or foreign equivalent in Business Analysis, Data Science, Applied Computer Science, Mathematics or related field and 4 years of experience as a Data Analyst, Business ...

Director, Data Science

Chicago, IL · On-site

$120K - $175K/yr

Director, Data Science The Data Science team is pivotal in the delivery of modern agency services ... A university degree in mathematics, computer science, statistics or related field, and 7-10 years ...

Data Understanding of Sales, Inventory, Store, Product and Promotion Data * Ability to translate ... Bachelor's degree or foreign equivalent required from an accredited institution. Will also consider ...

Data Understanding of Sales, Inventory, Store, Product and Promotion Data. * Ability to translate ... Bachelor's degree or foreign equivalent required from an accredited institution. Will also consider ...

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Showing results 1-20

Data Science Degree information

See Illinois salary details

$36.3K

$118.9K

$190.4K

How much do data science degree jobs pay per year?

As of May 28, 2026, the average yearly pay for data science degree in Illinois is $118,937.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,400.00 and $131,800.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Scientist, and why are they important?

To thrive as a Data Scientist, you need a strong background in mathematics, statistics, and programming, typically supported by a degree in data science, computer science, or a related field. Proficiency in technical tools such as Python or R, SQL, and machine learning frameworks, along with relevant certifications, is highly valued. Strong problem-solving abilities, effective communication, and curiosity help set apart top-performing data scientists. These skills are crucial for extracting actionable insights from data, collaborating with stakeholders, and driving data-driven decision-making.

What types of real-world projects or team collaborations can I expect to work on after earning a Data Science degree?

After earning a Data Science degree, you can expect to engage in a variety of real-world projects such as building predictive models, analyzing large datasets to uncover business insights, and developing data-driven solutions for organizational challenges. Data scientists often collaborate closely with cross-functional teams, including software engineers, business analysts, and domain experts, to translate complex data findings into actionable strategies. These collaborations not only enhance your technical skills but also provide valuable experience in communication and project management, which are essential for career growth in this field.

What is a Data Science degree?

A Data Science degree is an academic program that prepares students to analyze, interpret, and derive insights from complex data sets using statistical, computational, and machine learning techniques. The curriculum typically includes coursework in mathematics, statistics, computer science, and specialized data science methods. Graduates are equipped with the skills to work in a variety of industries, tackling real-world problems by leveraging data-driven decision making. This degree can be pursued at the undergraduate or graduate level, and often includes hands-on projects and internships.

Is data science dead in 10 years?

Data science is a growing field that is expected to remain relevant over the next decade, as organizations continue to rely on data analysis, machine learning, and statistical skills. Advances in automation and AI may change some roles, but the need for skilled data scientists to interpret complex data and develop models will persist. Continuous learning and proficiency with tools like Python, R, and SQL are essential for long-term career success in this field.

What is the difference between Data Science Degree vs Data Analyst?

AspectData Science DegreeData Analyst
Required CredentialsBachelor's or Master's in Data Science, Computer Science, or related fieldsBachelor's in Statistics, Mathematics, or related fields
Work EnvironmentResearch, modeling, developing algorithms, often in tech or finance industriesData cleaning, reporting, visualization, supporting business decisions
Employer & Industry UsageTech companies, finance, healthcare, academiaRetail, marketing, finance, healthcare

Data Science Degree programs focus on advanced analytics, machine learning, and programming, preparing individuals for complex modeling roles. Data Analysts typically handle data processing, visualization, and reporting to support decision-making. While both roles require strong analytical skills, Data Science degrees emphasize technical and statistical expertise, whereas Data Analysts focus on interpreting data for business insights.

What cities in Illinois are hiring for Data Science Degree jobs? Cities in Illinois with the most Data Science Degree job openings:
Infographic showing various Data Science Degree job openings in Illinois as of May 2026, with employment types broken down into 94% Full Time, and 6% Part Time. Highlights an 82% In-person, 6% Hybrid, and 12% Remote job distribution, with an average salary of $118,937 per year, or $57.2 per hour.
Data Engineer

$113.80K - $136.60K/yr

Other

This job post has expired today. Applications are no longer accepted.


Job description

Position Overview
The Data Engineer builds and scales enterprise data solutions within BCS' ecosystem to support Enterprise Analytics, operational reporting, and self-service business intelligence.
This role focuses on developing governed, high-performance, and reusable data assets aligned with enterprise data architecture standards. The Data Engineer plays a key role in enabling advanced analytics, including data exploration, feature engineering, statistical modeling, and AI-driven use cases.
This position works in close coordination with the Enterprise Data Architect and broader IT teams to ensure consistency, scalability, security, and alignment with BCS' long-term data strategy.
This role supports key enterprise initiatives including Data Enablement and AI-driven analytics.
This position will report to the Director of Data Engineering.
Essential Elements
List the duties and responsibilities the incumbent would be spending at least 15 - 20% of their time doing in this position.
  • Design ETL pipelines using Microsoft Fabric and other enterprise data platforms asappropriate.
  • Partner closely with the Enterprise Data Architect to align data models, pipelines, and storage patterns with enterprise data architecture standards
  • Manage andoptimizedata within Microsoft FabricOneLake, including data residency andshortcuts.
  • Develop andmaintaintransformation logic using Fabric Notebooks (PySpark/Spark SQL) across medallion architecture layers (bronze, silver, gold).
  • Design and implementefficientincremental data loading and change data capture strategies.
  • Partner with Analytics and business teams to deliver trusted, well-documented, and reusable datasets for reporting and advanced analytics
  • Collaborate with analytics and data science teams to operationalize models and integrate outputs into business workflow
  • Implement and enforce data governance standards, including data quality validation, lineage, classification, and access controls
  • Support Enterprise Analytics' use of AI techniques such as text extraction or natural language processing
  • Ensure compliance with data privacy and regulatory requirements (e.g., PHI/PII handling)
  • Prepare andmaintaindocumentation to ensure transparency, usability, and long-term maintainability
Requirements
Education and Certifications
Required - Bachelor of Science degree in Information Systems, Computer Science, Statistics, Data Science or other related field
Preferred - Relevant certifications in cloud, data engineering, or analytics platform
Experience
Required
  • At least5years of experience in a data engineering role
  • Advanced SQL skills for data transformation and modeling
  • Hands on experience with Microsoft Fabric Data Factory for orchestration and ingestion
  • Experience with medallion data architecture patterns
  • Experience implementing data validation and pipeline monitoring
  • Experience with ETL tools(e.gSSISor equivalent).
  • Working knowledge of .NET/C#, Python, APIs, version control, CI/CDpracticesand agile workflow
Preferred
  • Insurance industry experience
  • Collaboration with data science teams
  • Familiarity with Azure ecosystem (Azure SQL, Azure Functions, storage, etc.)
  • Experience with data modeling techniques (e.g., dimensional modeling, star schema)

Travel Required
Regular attendance in office as mandated by BCS HR policy