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Entry Level Data Science Jobs in Wheaton, IL (NOW HIRING)

Pwc

AI & GenAI Data Scientist - Manager

Chicago, IL · On-site

$99K - $232K/yr

Management Information Systems, Computer and Information Science, Systems Engineering, Mathematics ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Pwc

AI & GenAI Data Scientist - Manager

Rosemont, IL · On-site

$99K - $232K/yr

Management Information Systems, Computer and Information Science, Systems Engineering, Mathematics ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Pwc

AI & GenAI Data Scientist-Senior Associate

Chicago, IL · On-site

$77K - $202K/yr

Management Information Systems, Computer and Information Science, Systems Engineering, Mathematics ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Pwc

AI & GenAI Data Scientist-Senior Associate

Rosemont, IL · On-site

$77K - $202K/yr

Management Information Systems, Computer and Information Science, Systems Engineering, Mathematics ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

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All JobsData Science JobsEntry Level Data Science JobsEntry Level Data Science Jobs in Wheaton, IL

Entry Level Data Science information

See Wheaton, IL salary details

$10

$18

$26

How much do entry level data science jobs pay per hour?

As of Jun 16, 2026, the average hourly pay for entry level data science in Wheaton, IL is $18.41, according to ZipRecruiter salary data. Most workers in this role earn between $15.58 and $20.67 per hour, depending on experience, location, and employer.

Are there entry-level data science roles?

Yes, entry-level data science roles are available and typically require foundational skills in programming, statistics, and data analysis, often using tools like Python or R. These positions are suitable for recent graduates or those transitioning into data science and may involve internships or junior analyst roles to build experience.

Is 40 too late for data science?

Entry level data science roles are open to candidates of all ages, including those starting a career at 40 or older. Success depends on acquiring relevant skills such as programming, statistics, and data analysis, often through online courses or certifications, regardless of age.

What are entry level data science jobs?

Entry level data science jobs are positions designed for individuals who are starting their careers in the field of data science, often requiring minimal professional experience. These roles typically involve working with data collection, cleaning, and analysis, as well as assisting more senior data scientists with projects. Entry level data scientists are expected to have a foundational understanding of statistics, programming (often in Python or R), and basic machine learning concepts. They may work in various industries, helping organizations gain insights from data to support decision-making.

How do I become a data scientist with no experience?

To become an entry-level data scientist with no experience, focus on building foundational skills in programming (Python or R), statistics, and data analysis through online courses and tutorials. Gaining practical experience by working on personal projects, participating in competitions like Kaggle, and learning tools such as SQL and machine learning libraries can help demonstrate your abilities to employers.

What types of projects or tasks can I expect to work on as an entry-level data scientist?

As an entry-level data scientist, you'll typically work on tasks such as data cleaning, exploratory data analysis, and supporting the development of predictive models. You may also assist in preparing datasets, generating reports, and visualizing data for stakeholders. Collaboration with more senior data scientists and cross-functional teams like engineering or business analysts is common, giving you opportunities to learn and grow your technical and communication skills. These foundational projects are essential for building your expertise and preparing for more complex responsibilities as you advance in your career.

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

To thrive as an Entry Level Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, typically supported by a relevant degree such as computer science, mathematics, or statistics. Familiarity with technical tools like SQL databases, data visualization software (e.g., Tableau), and machine learning libraries (such as scikit-learn or TensorFlow) is commonly expected. Curiosity, problem-solving ability, and effective communication help you interpret data insights and collaborate with diverse teams. These skills ensure you can extract meaningful insights from data, contribute to data-driven decision-making, and grow within the analytics field.

What is the difference between Entry Level Data Science vs Data Analyst?

AspectEntry Level Data ScienceData Analyst
Required CredentialsBachelor's in CS, Statistics, or related field; some certificationsBachelor's in Business, Statistics, or related field; certifications optional
Work EnvironmentTech companies, startups, research labsBusiness, marketing, finance sectors
Employer & Industry UsageData-driven roles in tech and researchBusiness insights, reporting, and visualization
Common Search & ComparisonYesYes

Entry Level Data Science and Data Analyst roles often share similar educational backgrounds and work environments. However, data scientists typically focus on building models and advanced analytics, while data analysts concentrate on interpreting data and creating reports. Both roles are essential in data-driven organizations, but they differ in technical complexity and scope.

Can I get a data scientist job with no experience?

Entry-level data science positions often require some knowledge of programming, statistics, and data analysis tools like Python or R. While prior experience is not always mandatory, demonstrating relevant skills through projects, certifications, or internships can improve your chances of securing such roles.
What are the most commonly searched types of Data Science jobs in Wheaton, IL? The most popular types of Data Science jobs in Wheaton, IL are:
What cities near Wheaton, IL are hiring for Entry Level Data Science jobs? Cities near Wheaton, IL with the most Entry Level Data Science job openings:
Entry Level Data Science jobs near you
Infographic showing various Entry Level Data Science job openings in Wheaton, IL as of June 2026, with employment types broken down into 93% Full Time, and 7% Part Time. Highlights an 86% In-person, and 14% Remote job distribution, with an average salary of $38,302 per year, or $18.4 per hour.
Entry level software developer/Data engineer

Entry level software developer/Data engineer

SynergisticIT

Chicago, IL

$118K - $141K/yr

Other

Posted 17 days ago

Job description

"From Another Industry to Tech: Convert Your Experience Into a Tech Offer."
Breaking into tech from another industry can feel intimidating-until you realize you already have advantages many entry-level candidates don't. If you're coming from business operations, finance, healthcare, education, QA, customer support, project management, logistics, or even sales, you've likely built skills that translate well into tech teams: problem solving, stakeholder communication, process thinking, and real-world accountability. What you may be missing is structured technical depth and an interview-ready portfolio. That's where SynergisticIT's JOPP comes in: it's designed to help you bridge from "capable professional" to "hire-ready engineer or data professional."
Since 2010, SynergisticIT has supported thousands of candidates into full-time roles with major employers such as Google, Apple, PayPal, Visa, Western Union, Wells Fargo, Client, Walmart Labs, Client, Banking, Client, and more-often at $95k to $154k depending on role and stack. JOPP is built around one goal: close the gap between what tech employers expect and what jobseekers typically have after self-study or training-only bootcamps.
What roles can career switchers target?
SynergisticIT typically supports candidates targeting roles like entry-level software programmer, Java full stack developer, Python/Java developer, DevOps engineer, data analyst, BI analyst, data engineer, data scientist, and machine learning/AI engineer-based on client needs. The program's focus areas are clear: Java / Full Stack / DevOps and Data Analytics / Data Engineering / Data Science / ML/AI.
Why "learning" isn't enough when switching careers
Most career switchers try to piece together skills from Udemy/Coursera, free tutorials, and quick bootcamps. That can build familiarity-but employers hire for job-ready depth. You need:
  • Strong fundamentals (programming + data concepts)
  • Real projects (not tutorials)
  • A clear role narrative ("I'm targeting X with Y stack")
  • Interview preparation and repetition
  • A plan for getting interviews, not just learning skills
SynergisticIT sees many candidates arrive after trying other paths. In fact, it often notes that about 30% of JOPP candidates have already tried bootcamps, online courses, or university bootcamps and didn't secure jobs-because those options focused on learning but not the job-search execution and readiness.
Please read our blogs
Why do Tech Companies not Hire recent Computer Science Graduates | SynergisticIT
The $100k H1B Filing Fee: Implications on U.S. Tech Employment | SynergisticIT
Wage-Based H-1B Filing
What Recruiters Look for in Junior Developers | SynergisticIT
Software engineering or Data Science as a career?
How OPT Students Can Land Tech Jobs - SynergisticIT
How JOPP helps convert your background into a tech story
If you come from business, you can present "domain + tech" as a strength. If you come from QA or project roles, you already understand how software teams operate. JOPP helps you fill technical gaps while shaping a profile that resonates with employers. This includes structured projects, tool exposure, interview readiness, and placement support.
International candidates and documentation support
For F1/OPT candidates, employment timelines matter. SynergisticIT provides guidance around STEM extension and process support related to H-1B and Green Card filing once employed (as applicable through employers).
Want ROI context?
ROI Blog: https://www.synergisticit.com/roi-of-job-placement-program/
If you want to explore the program directly, here are the key links:
  • Job Placement Program (JOPP):
  • Java Job Placement Program
  • Data Science / Data Jobs Program
  • Event videos (OCW, JavaOne, Gartner):
  • USA Today feature
  • Contact Us: https://www.synergisticit.com/contact-us/
You don't have to start over-you just have to start with the right roadmap.

Apply