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Data Science Machine Learning Jobs in Illinois (NOW HIRING)

This team utilizes the power of data science and machine learning techniques to address the diverse business questions and challenges facing Ulta Beauty. As a Data Scientist, you will succeed by ...

Data Scientist

Bolingbrook, IL ยท On-site

$102K - $130K/yr

This team utilizes the power of data science and machine learning techniques to address the diverse business questions and challenges facing Ulta Beauty. As a Data Scientist, you will succeed by ...

This team utilizes the power of data science and machine learning techniques to address the diverse business questions and challenges facing Ulta Beauty. As a Data Scientist, you will succeed by ...

The Director, Data (MarTech) is responsible for applying data exploration and visualization, machine learning and artificial intelligence, and other data science techniques to explore, create, and ...

Data analysts/Data Scientists * Machine Learning engineers for full time positions with clients. Who should apply? Recent computer science/engineering/mathematics/statistics or science graduates or ...

About the Opportunity At Wonder Data Science, our mission is to build data science and machine learning systems that improve how our marketplace operates, how customers experience the platform, and ...

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Showing results 1-20

Data Science Machine Learning information

See Illinois salary details

$36.3K

$118.9K

$190.4K

How much do data science machine learning jobs pay per year?

As of Jun 29, 2026, the average yearly pay for data science machine learning 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.

Which has more salary, CS or AI?

Data Science and Machine Learning roles in AI generally have higher salaries than traditional computer science positions due to specialized skills in deep learning, neural networks, and advanced algorithms. AI roles often require expertise in programming languages like Python and frameworks such as TensorFlow, which are highly valued in the job market. Salaries vary by experience, location, and industry, but AI-focused positions tend to offer higher compensation on average.

What are the key skills and qualifications needed to thrive as a Data Science Machine Learning professional, and why are they important?

To thrive as a Data Science Machine Learning professional, you need a strong background in statistics, programming (usually Python or R), and a solid understanding of machine learning algorithms, often supported by a degree in computer science, mathematics, or a related field. Familiarity with tools like TensorFlow, scikit-learn, SQL databases, and cloud platforms, as well as certifications such as AWS Certified Machine Learning, are typically valuable. Critical thinking, problem-solving, and effective communication are vital soft skills for interpreting data and collaborating with stakeholders. These skills enable professionals to develop robust models, extract actionable insights, and drive data-driven decision-making in organizations.

What engineers make $500,000?

Senior data science and machine learning engineers with extensive experience, advanced skills in programming, statistical analysis, and deep learning, and often working in high-demand industries or at large tech companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at executive or specialized levels.

What are some common challenges faced when deploying machine learning models as a Data Science Machine Learning professional?

A frequent challenge in this role is bridging the gap between building accurate models in a controlled environment and deploying them effectively in production systems. Issues such as data drift, model performance degradation, and integration with existing IT infrastructure often arise. Collaboration with engineering and IT teams is crucial to ensure models are scalable, maintainable, and secure. Regular monitoring and updating of deployed models are also essential responsibilities to sustain their value to the business.

What is the difference between Data Science Machine Learning vs Data Analyst?

AspectData Science Machine LearningData Analyst
Required SkillsProgramming (Python, R), statistics, machine learning algorithmsData visualization, SQL, basic statistics
Work EnvironmentDeveloping models, coding, experimenting with algorithmsData reporting, dashboard creation, data cleaning
Industry UsageTech, finance, healthcare, where predictive models are neededBusiness intelligence, marketing, operations

Data Science Machine Learning professionals focus on building predictive models and algorithms using programming and advanced statistics, often working on complex projects. Data Analysts primarily interpret data through visualization and reporting to support business decisions. While both roles require data skills, Data Science Machine Learning involves more technical programming and modeling, whereas Data Analysts focus on data interpretation and presentation.

Do data scientists work with machine learning?

Data scientists often work with machine learning as a core part of their role, developing models to analyze data and make predictions. They use tools like Python, R, and libraries such as scikit-learn or TensorFlow to build and deploy machine learning algorithms. Knowledge of statistics, programming, and data manipulation is essential for this work.

What is data science machine learning?

Data science machine learning refers to the use of algorithms and statistical models to analyze and draw insights from complex data sets. In this field, professionals use machine learning techniques to build predictive models, automate decision-making processes, and uncover patterns in data. Machine learning is a core component of data science, enabling systems to improve their performance over time without being explicitly programmed. Data scientists with machine learning expertise are in high demand across industries like healthcare, finance, and technology.

Which 3 jobs will survive AI?

Data science and machine learning roles are expected to persist as they require complex problem-solving, domain expertise, and creativity that AI tools currently cannot fully replicate. Jobs involving strategic decision-making, ethical considerations, and interpersonal skills, such as data analysts, AI ethics specialists, and AI system trainers, are also likely to remain in demand. Continuous learning and proficiency with AI tools will be essential for these roles to adapt and thrive.
What cities in Illinois are hiring for Data Science Machine Learning jobs? Cities in Illinois with the most Data Science Machine Learning job openings:
Infographic showing various Data Science Machine Learning job openings in Illinois as of June 2026, with employment types broken down into 59% Full Time, 37% Part Time, 2% Contract, and 2% Nights. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $118,937 per year, or $57.2 per hour.
Machine Learning / Data Science Engineer

Machine Learning / Data Science Engineer

CapTech Consulting

Chicago, IL โ€ข On-site

$118K - $141K/yr

Other

Medical, Retirement, PTO

Posted 12 days ago


Job description

Machine Learning / Data Science Engineer

CapTech is an award-winning consulting firm that collaborates with clients to achieve what's possible through the power of technology. At CapTech, we're passionate about the work we do and the results we achieve for our clients. From the outset, our founders shared a collective passion to create a consultancy centered on strong relationships that would stand the test of time. Today we work alongside clients that include Fortune 100 companies, mid-sized enterprises, and government agencies, a list that spans across the country.

Job Description

CapTech Machine Learning Engineers are responsible for designing and implementing data-driven solutions for our clients, with a specific focus on building and deploying scalable machine learning systems in enterprise environments. CapTech employees enjoy a collaborative environment and have many opportunities to learn from and share knowledge with other CapTech analysts, architects, and our clients.

Specific responsibilities for the Machine Learning Engineer position include:

  • Strategizing with clients, data scientists, engineers, and other members of cross-functional teams to implement end-to-end machine learning solutions and identify new machine learning and data science approaches to meet business needs
  • Deconstructing client needs into data-driven processes/models and analytical measures.
  • Analyzing and transforming large datasets hosted on a variety of enterprise-level data platforms (e.g., AWS, Azure, GCP).
  • Designing, developing, and deploying advanced analytical solutions leveraging client data (e.g., recommender systems, natural language processing, risk scoring).
  • Productionizing ML systems with a focus on optimization and scalability to satisfy clients' requirements.
  • Growing CapTech's Machine Learning and Data Science practices through delivering client presentations, writing proposals, attending various business development events, and leading teams of junior data scientists and engineers.
Qualifications
  • Bachelor's degree or equivalent combination of education and experience.
  • Hands-on experience manipulating and analyzing large (multi-billion record) data sets.
  • Hands-on experience developing data-driven solutions using Python, Scala, or similar languages.
  • Proficiency leveraging SQL, Spark, NoSQL, and/or cloud data processing frameworks in a production setting.
  • Proficiency with containerization (e.g., Docker) and microservices.
  • Proficiency with data warehousing tools/environments such as Snowflake, Databricks, Azure SQL, Amazon RDS
  • Comfort and proficiency in framing data-driven problems from cross-industry business requirements.
  • Experience applying analytical methods across multiple business domains (e.g., customer analytics, marketing, finance, digital channels)
  • Hands-on experience implementing production-scale machine learning systems in one or more domains (i.e., personalization, natural language processing, computer vision).
  • Knowledge of DevOps and automation best practices.
  • Knowledge of statistics and statistical modeling methods.
  • Knowledge of model management and model versioning best practices.
  • Experience working with LLMs (e.g., GPT, Claude, Mistral, etc.) in production setting
  • Experience with prompt engineering, MCP and RAG, and agentic AI architectures
  • Strong understanding of conversational UX and prompt evaluation metrics
  • Experience with agentic frameworks in practice (langchain, n8n, pydantic, etc.)
  • Experience with multi-agent orchestration
Additional Information

We want everyone at CapTech to be able to envision a lasting and rewarding career here, which is why we offer a variety of career paths based on your skills and passions. You decide where and how you want to develop, and we help get you there with customizable career progression and a comprehensive benefits package to support you along the way. Alongside our suite of traditional benefits encompassing generous PTO, health coverage, disability insurance, paid family leave and more, we've launched extended benefits to help meet our employees' needs.

  • CapTech is committed to providing a flexible work environment and helping our employees achieve a work-life balance that suits their individual needs. Employees must be available to work onsite in a client location or a CapTech office as requested. We allow CapTech employees to work remotely when compatible with CapTech and client needs.
  • Learning & Development โ€“ Programs offering certification and tuition support, digital on-demand learning courses, mentorship, and skill development paths
  • Modern Health โ€“A mental health and well-being platform that provides 1:1 care, group support sessions, and self-serve resources to support employees and their families through life's ups and downs
  • Carrot Fertility โ€“Inclusive fertility and family-forming coverage for all paths to parenthood โ€“ including adoption, surrogacy, fertility treatments, pregnancy, and more โ€“ and opportunities for employer-sponsored funds to help pay for care
  • Fringe โ€“A company paid stipend program for personalized lifestyle benefits, allowing employees to choose benefits that matter most to them โ€“ ranging from vendors like Netflix, Spotify, and GrubHub to services like student loan repayment, travel, fitness, and more
  • Employee Resource Groups โ€“ Employee-led committees that embrace and incorporate diversity and inclusion into our day-to-day operations
  • Philanthropic Partnerships โ€“ Opportunities to engage in partnerships and pro-bono projects that support our communities.
  • 401(k) Matching โ€“ Generous matching and no vesting period to help you continue to build financial wellness

CapTech is an equal opportunity employer committed to fostering a culture of equality, inclusion and fairness โ€” each foundational to our core values. We strive to create a diverse environment where each employee is encouraged to bring their unique ideas, backgrounds and experiences to the workplace. For more information about our Diversity, Inclusion and Belonging efforts, click HERE. As part of this commitment, CapTech will ensure that persons with disabilities are provided reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact Laura Massa directly via email lmassa@captechconsulting.com.

CapTech supports Equal Pay for all. In addition, in the State of Illinois we are committed to Equal Pay for ALL in accordance with the Illinois Equal Pay Act. The base pay range for this role is: $90,000 - $200,000k.

At this time, CapTech cannot transfer nor sponsor a work visa for this position. Applicants must be authorized to work directly for any employer in the United States without visa sponsorship.