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Data Science Assistant Jobs in Wisconsin (NOW HIRING)

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 ...

... 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 ...

... 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 ...

... 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 ...

WI · On-site

$140 - $190/hr

The Purpose of Your Role This individual will lead high‑profile applied data science and ... assistants, recommender systems, and anomaly detection. The successful candidate must be ...

New

WI · On-site

$80 - $120/hr

Assistant Professor - Data Science (Trauma, Critical Care, and Healthcare Disparities Research) Division: Surgery Work Arrangement: Location: Houston, TX | Salary Range: FLSA Status: Exempt Baylor ...

... science and machine learning initiatives * Assist in developing analytical approaches and preparing data for more advanced modeling initiatives Ideal candidates will possess a bachelor's degree in ...

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 ...

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 ...

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Data Science Assistant information

What is a data science assistant?

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?

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.

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 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 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:

Infographic showing various Data Science Assistant job openings in Wisconsin as of August 2026, with employment types broken down into 5% Internship, 80% Full Time, 11% Part Time, 2% Temporary, and 2% Contract. Highlights an 94% In-person, and 6% Remote job distribution.

Data Science Analyst

Generac

Waukesha, WI • On-site

Full-time

Re-posted 17 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

356th of 495 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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