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Entry Level Data Science Jobs in Kenosha, WI (NOW HIRING)

Snap-on Inc

Support Engineer

Kenosha, WI · On-site

Overview We are looking for an Entry-Level Support Engineer with 2-3 years of experience to support ... Investigate data issues using SQL (joins, filtering, aggregations) to identify root causes

Snap-on Inc

Support Engineer

Kenosha, WI

Overview We are looking for an Entry-Level Support Engineer with 2-3 years of experience to support ... Investigate data issues using SQL (joins, filtering, aggregations) to identify root causes

Snap-on Inc

Support Engineer

Kenosha, WI

We are looking for an Entry-Level Support Engineer with 2-3 years of experience to support and ... Investigate data issues using SQL (joins, filtering, aggregations) to identify root causes

All JobsData Science JobsEntry Level Data Science JobsEntry Level Data Science Jobs in Kenosha, WI

Entry Level Data Science information

See Kenosha, WI salary details

$10

$18

$26

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

As of Aug 1, 2026, the average hourly pay for entry level data science in Kenosha, WI is $18.46, according to ZipRecruiter salary data. Most workers in this role earn between $15.62 and $20.72 per hour, depending on experience, location, and employer.

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 languages like Python or R, and learn data analysis and visualization tools such as SQL and Tableau. Completing online courses, working on personal projects, and participating in competitions like Kaggle can demonstrate your abilities and help you gain practical experience. Earning relevant certifications and creating a strong portfolio can improve your chances of entering the field.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or features. Entry level data scientists often focus on identifying the most impactful variables or tasks to optimize model performance and efficiency.

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 languages like Python or R, and familiarity with data analysis tools. While prior experience is not always mandatory, demonstrating relevant skills through projects, certifications, or coursework can improve your chances of securing an entry-level role.
What are popular job titles related to Entry Level Data Science jobs in Kenosha, WI? For Entry Level Data Science jobs in Kenosha, WI, the most frequently searched job titles are:
What job categories do people searching Entry Level Data Science jobs in Kenosha, WI look for? The top searched job categories for Entry Level Data Science jobs in Kenosha, WI are:
What cities near Kenosha, WI are hiring for Entry Level Data Science jobs? Cities near Kenosha, WI 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 Kenosha, WI as of July 2026, with employment types broken down into 1% As Needed, 79% Full Time, 16% Part Time, 1% Temporary, 2% Contract, and 1% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $38,407 per year, or $18.5 per hour.

Associate Scientist I - Analytical Chemistry

DivIHN Integration Inc

Round Lake, IL • On-site

Contractor

Re-posted 2 days ago

Job description

DivIHN (pronounced “divine”) is a CMMI ML3-certified Technology and Talent solutions firm. Driven by a unique Purpose, Culture, and Value Delivery Model, we enable meaningful connections between talented professionals and forward-thinking organizations. Since our formation in 2002, organizations across commercial and public sectors have been trusting us to help build their teams with exceptional temporary and permanent talent.

Visit us at https://divihn.com/find-a-job/ to learn more and view our open positions.

 
Please apply or call one of us to learn more

For further inquiries regarding the following opportunity, please contact our Talent Specialist, Hema at (630) 847-0275
 
Title: Associate Scientist I - Analytical Chemistry
Duration: 12 Months
Location: On-site at Round Lake, IL (Local Candidates Only IL or WI)
Schedule: 8 AM - 5 PM CST
 
Only W2 candidates are eligible for this position. Third-party or C2C candidates will not be considered.
 
Description:
Looking for an Entry-Level Chemist, including recent graduates or candidates with 0–2 years of experience, who are eager to learn and grow in a laboratory environment. The candidate will perform routine wet chemistry testing (pH, UV, titrations, particle analysis) and support quality control processes. As an Associate Scientist I, your work contributes directly to making a significant impact on others. We collaborate cross-functionally and lead by influence. As a key part of projects, our research and development team is responsible for delivering results to drive decisions and ensure safety of our existing and new products. We work on products that make a meaningful difference in others' lives. When you join Client, you'll use your analytical approach to identify risks and opportunities for innovation. Agile and willing to take action, you stay calm under pressure!
 
What you’ll be doing:
• Conduct critical chemical and physical analyses on finished product R&D stability samples. May also support testing of raw materials, initial, in-process, and final product samples from manufacturing facilities or other R&D initiatives. Work under minimum supervision.
• Perform chemical assays requiring precise analytical skills and understanding of chemistry principles.
• Complete all testing, including special project/protocol testing in a timely and appropriate manner to meet project schedules.
• Maintain data integrity and ensure compliance with company SOPs and specifications, FDA, cGxP, and QSR regulations.
• Collaborate with other functions/departments to solve problems, increase efficiency, improve quality and provide product support.
• Use sophisticated laboratory instrumentation (HPLC, pH, UV, titrations, Particle, TOC, Flame photometry, etc) and computer systems to collect and record data.
• Follow, understand and comply with Client SOP’s and policies on cGMP’s and safety. Maintain a clean, safe and organized lab area, and potentially assume responsibility to ensure that others maintain their lab areas.
• Maintain laboratory safety requirements, perform equipment maintenance/calibration, and troubleshoot instrumentation. Basic understanding of laboratory instruments and testing methods
 
What you’ll bring:
• Bachelor's degree in relevant scientific discipline (e.g. chemistry, pharmaceutical sciences, biology) 6 months or more of experience
• Analytical chemistry instrumentation experience with pH, UV, titrations, Particle, TOC is preferred but not required.
• Must have experience in a regulated environment, strong technical problem-solving skills, good oral and written communication skills, willingness to learn, self-motivated, strong analytical skills and be detail oriented.
•0–2+ years of laboratory experience (academic or industry) and hands-on experience or research, academic exposure to wet chemistry techniques
• Electronic Lab Notebook experience is preferred but not required.
• Pharmaceutical GMP laboratory experience is desired.
• Empower experience is preferred
• Must be able to handle multiple tasks concurrently and in a timely fashion.
• Possess relevant laboratory/technical, writing, and computer skills.
• Ability to organize and communicate complex information effectively with managers and peers
•Ability to work onsite full-time
 
Physical Activities and Requirements:
• Must be able to handwrite and use computers for the majority of the workday
• Must be able to transfer materials, mix solutions/product(s), open products, and perform laboratory testing
• May require standing for extended periods
• Must be able to lift up to 10 pounds routinely
• Must not be color blind
 
This work is subject to hazards, including exposure to chemicals and drug products. Penicillin and Cephalosporin containing products and/or materials may be present in the laboratory.
 
Interview: 1 round Onsite

About us:
DivIHN, the 'IT Asset Performance Services' organization, provides Professional Consulting, Custom Projects, and Professional Resource Augmentation services to clients in the Mid-West and beyond. The strategic characteristics of the organization are Standardization, Specialization, and Collaboration.

DivIHN is an equal opportunity employer. DivIHN does not and shall not discriminate against any employee or qualified applicant on the basis of race, color, religion (creed), gender, gender expression, age, national origin (ancestry), disability, marital status, sexual orientation, or military status.