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Data Science Assistant Jobs in Wisconsin (NOW HIRING)

Generac

Data Science Analyst

Waukesha, WI · On-site

In the role of Data Science Analyst working onsite in Waukesha, Wisconsin you will be part of the ... The candidate will work on Enterprise data platform and other analytical projects as needed, assist ...

Innovizant LLC

Data Scientist

Madison, WI · On-site

... data science, data engineering and decision science to provide winning actionable insights ... Some of our sur accelerators and solution frameworks assist our clients including FIN-CDO (which ...

Innovizant LLC

Data Scientist

Madison, WI

... data science, data engineering and decision science to provide winning actionable insights ... Some of our sur accelerators and solution frameworks assist our clients including FIN-CDO (which ...

KOHLS

Data Scientist (Remote)

Menomonee Falls, WI · On-site

... data science team and cross-functional partners to solve business challenges and promote data-driven decision making with advanced data analysis and machine learning. What You'll Do * Assist in ...

Innovizant LLC

Spark Expert (Direct Client)

Madison, WI · On-site

Innovizant made up of exceptional data scientists and domain experts with a great experience in Our ... Some of our sur accelerators and solution frameworks assist our clients including FIN-CDO (which ...

CTech Manufacturing

Data Engineer

Schofield, WI · On-site

$114K - $137K/yr

... Assist in transitioning ETL workflows into scalable, efficient ELT processes Work with SQL Server ... Associate's degree or higher in Computer Science, Data Science, Information Systems, or a related ...

Qualysoft

... Data-Science- und KI-Projekten. Rahmenbedingungen Start: ASAP Laufzeit: Ende 2026, Verlangerung ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Howard

Research Assistant

Downing, WI · On-site

$21 - $31/hr

The candidate should be well-informed about the scientific method, human subjects research, and data analysis using computational and statistical techniques. The Research Assistant will assist in ...

Kwik Trip, Inc.

Master Data Analyst

La Crosse, WI · On-site

$66K - $99K/yr

Implement and manage MDM best-record and matching processes to improve data quality. * Assist in ... Bachelor's degree in computer science, data science, or a related field, or equivalent experience.

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Data Science Assistant information

What are Data Science Assistants?

Data Science Assistants are professionals who support data scientists and analytics teams by handling tasks such as data collection, data cleaning, preparing datasets, conducting preliminary analyses, and creating visualizations. They often work with large datasets, assist in maintaining data integrity, and help automate routine processes. Their role allows data scientists to focus on more complex modeling and analytical work, making the overall workflow more efficient. Data Science Assistants typically have a foundational understanding of statistics, programming (such as Python or R), and data management tools.

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

To thrive as a Data Science Assistant, you need a solid understanding of statistics, data analysis, and programming (often with a background in mathematics, computer science, or a related field). Familiarity with tools like Python or R, data visualization software, and experience with databases or spreadsheet systems are typically required. Attention to detail, strong problem-solving abilities, and effective communication set outstanding candidates apart. These skills are crucial for supporting data-driven decision-making and ensuring accurate, actionable insights for organizations.

Is 40 too late for data science?

Data Science Assistants and other data science roles do not have strict age limits; many professionals start or transition into data science later in life. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, which can be learned at any age through online courses, certifications, and practical experience.

How does a Data Science Assistant typically collaborate with data scientists and other team members on projects?

As a Data Science Assistant, you will frequently support data scientists by preparing datasets, conducting preliminary data analysis, and creating visualizations. You will often work closely with analysts, engineers, and subject matter experts to gather requirements and ensure data is cleaned and formatted appropriately. Collaboration is a key part of the role, as you may participate in team meetings, share findings, and help with documentation to keep projects running smoothly. This supportive environment provides an excellent opportunity to learn from experienced professionals and gain exposure to the full data science workflow.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of the results come from 20% of the efforts or data. Data scientists often use this concept to focus on the most impactful features, data subsets, or tasks to improve model performance efficiently.

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

AspectData Science AssistantData Analyst
Required CredentialsBachelor's in Data Science, Statistics, or related fieldBachelor's in Statistics, Mathematics, or related field
Work EnvironmentTech companies, research labs, data-driven departmentsBusiness, finance, marketing, healthcare sectors
Employer & Industry UsageUsed in data science teams for supporting models and analysisUsed across industries for interpreting data and generating reports

While both roles involve working with data, a Data Science Assistant typically supports data science projects, focusing on data preparation and model testing. A Data Analyst primarily interprets data to generate insights and reports. The roles overlap in skills and work environments but differ in their core responsibilities and focus areas.

What do data assistants do?

Data Science Assistants support data analysis by collecting, cleaning, and organizing data sets. They often use tools like Excel, SQL, or Python to prepare data for modeling and reporting, assisting data scientists and analysts in project workflows.

Can I get a data scientist job with no experience?

Entry-level data science assistant roles often do not require prior experience, but candidates typically need a strong foundation in programming (such as Python or R), statistics, and data analysis. Gaining relevant skills through online courses, certifications, or personal projects can improve chances of securing such positions.
What are the most commonly searched types of Data Science jobs in Wisconsin? The most popular types of Data Science jobs in Wisconsin are:
What are popular job titles related to Data Science Assistant jobs in Wisconsin? For Data Science Assistant jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Data Science Assistant jobs in Wisconsin look for? The top searched job categories for Data Science Assistant jobs in Wisconsin are:
Data Science Assistant jobs near you
Infographic showing various Data Science Assistant job openings in Wisconsin as of July 2026, with employment types broken down into 1% As Needed, 75% Full Time, 20% Part Time, 1% Temporary, and 3% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution.

Data Science Analyst

Generac

Waukesha, WI • On-site

Full-time

Posted 26 days ago

Generac Power Systems rating

7.0

Company rating: 7.0 out of 10

Based on 66 frontline employees who took The Breakroom Quiz

350th of 487 rated machine equipment manufacturers

Job description

We believe power is a promise - a shared commitment to be there for others when it matters most.

For more than 65 years, we've turned big ideas into solutions that help protect homes, strengthen businesses and build a more resilient, efficient, sustainable energy future.


Ready to Power a Smarter World with us?


In the role of Data Science Analyst working onsite in Waukesha, Wisconsin you will be part of the Data Analytics and Business Intelligence team.

The Data Science Analyst is responsible for the analysis of structured and unstructured data using various techniques, e.g. statistical analysis, explanatory and predictive modeling, data mining. The candidate will determine best practices and develop actionable insights and recommendations for the current operations or issues and works closely with the business functional team to identify analytical requirements. The candidate will work on Enterprise data platform and other analytical projects as needed, assist in implementing or developing systems to capture operational information, and may assist less experienced analysts. The candidate must have familiarity with the manipulation of unstructured data in a data analytics environment, and the use of open-source tools, cloud computing, machine learning and data visualization and appropriate, relevant programming languages.

*This is not a remote role, the ideal candidate will need to be located in Wisconsin, due to this position being onsite and reporting into our Waukesha Headquarters*

Minimum Qualifications:

  • Bachelor Degree

  • 1 year work experience in Math, Statistics, or Computer Science

Preferred Qualifications:

  • Relational database experience & Experience query databases (ex: SQL, MySql).

  • Experience with one or more statistical analysis tools (ex: MatLab, MiniTab, SPSS, or R).

  • Experience with statistical analysis languages (ex: R, Python, SQL).

  • Experience on using the cloud platform (ex Azure, AWS..)

  • Experience with building agents using Microsoft CoPilot, and other solution paths

Essential Duties:

  • Develop and analyze various data to support Enterprise Transformation initiatives and AI use cases

  • Supports data preparation for analytic efforts by cleaning data to ensure quality and accuracy based on provided guidelines; and consolidating data.

  • Translating business requirements; informing data/information needs and data collection methods

  • Create custom data models & create pipelines and algorithms as needed & produce Data insights

  • Assists with data and information gathering for targeted variables in an established systematic fashion by cleaning and organizing data; querying, merging, and extracting data across sources; completing routine data refresh and update; and providing user support and documentation.

  • Supporting end-users; and documenting processes and deliverables

  • Ongoing reports highlighting the initiative progress and successes.

Knowledge and Skills:

  • Ability to write complex SQL queries, data visualization

  • Proficiency in database applications and MS Office with excellent Excel skills.

  • Requires excellent analytical, organization, project management, communication, presentation and people skills with a variety of audiences, up to and including, the executive level.

  • Ability to simplify complex findings to develop unique, practical solutions.

  • Able to understand various data structures and common methods in data transformation.

  • Excellent pattern recognition and predictive modeling skills.

  • Cross/multi-functional understanding of industry, company, and products to enable identification of assumptions and events, and qualification of related risks and opportunities.

  • Self-motivated and able to work with minimal direction

#LI-BB1

Physical Demands: While performing the duties of this job, the employee is regularly required to talk and hear; and use hands to manipulate objects or controls. The employee is regularly required to stand and walk. On occasion, the incumbent may be required to stoop, bend, or reach above the shoulders. The employee must occasionallylift upto 25 pounds. Specific conditions of this job are typical of frequent and continuous computer-based work requiring periods of sitting, close vision, and the ability to adjust focus. Occasional travel.

"We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, disability status, protected veteran status, or any other characteristic protected by law."

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