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Data Scientist Project Manager Jobs in Wisconsin

We are looking for someone that leads data science projects from start to finish, defining the problem, identifying opportunities building proofs of concept and implements them as a data product. You ...

... management of forgings, automated characterization methods, and design and improvement of ... Build models and optimization tools to support large scale projects that utilize online, offline ...

... management of forgings, automated characterization methods, and design and improvement of ... Build models and optimization tools to support large scale projects that utilize online, offline ...

Project Management: A Data Science Lead should have strong project management skills, including the ability to prioritize tasks, manage timelines, and ensure that projects are completed on time and ...

Project Management: A Data Science Lead should have strong project management skills, including the ability to prioritize tasks, manage timelines, and ensure that projects are completed on time and ...

Project Management: A Data Science Lead should have strong project management skills, including the ability to prioritize tasks, manage timelines, and ensure that projects are completed on time and ...

Ability to lead projects or workstreams * Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment * Strong interpersonal skills and professional demeanor * Ability to ...

... management of forgings, automated characterization methods, and design and improvement of ... Build models and optimization tools to support large scale projects that utilize online, offline ...

However, the biggest challenge during managing this data comes across in the terms of 'Value Realization'. The true measure of success is to be able to put the data science insights into actionable ...

This position will serve as a data science subject matter expert to enhance UW-CTRI's capacity to ... The Scientist may contribute clinical research projects to across the translational spectrum of ...

However, the biggest challenge during managing this data comes across in the terms of 'Value Realization'. The true measure of success is to be able to put the data science insights into actionable ...

Document projects, including business objectives, data gathering and processing, leading approaches ... Supply chain management * Marketing models * Logistics experience

This individual will be leading, assigning and managing the execution of projects and will not be a ... in data science-specific roles, with demonstrated experience working in roles that require ...

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Data Scientist Project Manager information

What are the key skills and qualifications needed to thrive as a Data Scientist Project Manager, and why are they important?

To thrive as a Data Scientist Project Manager, you need a solid background in data science, analytics, and project management, often supported by degrees in computer science, statistics, or business and certifications like PMP or Agile. Familiarity with tools such as Python, R, SQL, project management software (e.g., Jira, Trello), and cloud platforms is crucial. Excellent communication, leadership, and problem-solving abilities help bridge gaps between technical teams and stakeholders. These skills ensure successful project delivery by aligning data-driven insights with business objectives and effective team coordination.

What is a Data Scientist Project Manager?

A Data Scientist Project Manager is a professional who oversees data science projects from conception through completion, ensuring that project goals align with business objectives. They bridge the gap between data science teams and stakeholders, managing timelines, resources, and communication. In addition to technical knowledge in data science and analytics, they possess strong project management skills to coordinate tasks, mitigate risks, and deliver results. Their role is essential for translating complex data-driven insights into actionable business strategies. They often use methodologies like Agile or Scrum to guide project workflows and adapt to changing requirements.

Can a data scientist become a project manager?

A data scientist can become a project manager by developing skills in leadership, communication, and project planning, often supplemented with certifications like PMP. Transitioning typically involves gaining experience in managing projects and understanding business objectives alongside technical expertise.

Is AI replacing data scientists?

AI is transforming the role of data scientists by automating routine tasks like data cleaning and basic analysis, but it does not replace the need for skilled professionals to interpret complex data, develop models, and make strategic decisions. Data scientists are increasingly required to work alongside AI tools, focusing on problem-solving, domain expertise, and model validation. The demand for data science skills remains strong as organizations seek to leverage AI effectively.

What is the difference between Data Scientist Project Manager vs Data Analyst Project Manager?

AspectData Scientist Project ManagerData Analyst Project Manager
Required CredentialsBachelor's/Master's in Data Science, Analytics, or related fields; certifications like PMP or AgileBachelor's in Data Analysis, Business, or related fields; certifications like PMP or Agile
Work EnvironmentLeads data science projects, collaborates with data scientists and engineersManages data analysis projects, works with analysts and business teams
Employer & Industry UsageTech companies, finance, healthcare, industries with advanced analyticsRetail, marketing, finance, industries relying on data reporting

The main difference is that Data Scientist Project Managers oversee data science initiatives involving complex modeling and algorithms, while Data Analyst Project Managers focus on managing data reporting and analysis projects. Both roles require project management skills and relevant certifications, but their technical focus and team collaboration differ.

How do Data Scientist Project Managers typically balance technical data work with project management responsibilities?

Data Scientist Project Managers often split their time between hands-on data analysis and overseeing project progress. They commonly coordinate with cross-functional teams, set project timelines, and ensure that data solutions align with business objectives while occasionally contributing code or analytical insights. Effective communication and time management are essential, as they must bridge the gap between technical teams and stakeholders. This dual responsibility offers exposure to both technical growth and leadership development, making it ideal for professionals seeking advancement into higher management roles.

What is a data science project manager?

A data science project manager oversees data-driven projects, coordinating teams of data scientists and analysts to ensure timely delivery of insights and solutions. They manage project scope, timelines, and resources, often utilizing tools like project management software and requiring knowledge of data science methodologies and business objectives.

Is 40 too late for data science?

For a Data Scientist Project Manager, age is not a barrier to entering or advancing in the field. Success depends on skills, experience, and continuous learning, such as mastering data analysis tools and programming languages like Python or R, regardless of age.
What are popular job titles related to Data Scientist Project Manager jobs in Wisconsin? For Data Scientist Project Manager jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Data Scientist Project Manager jobs in Wisconsin look for? The top searched job categories for Data Scientist Project Manager jobs in Wisconsin are:
What cities in Wisconsin are hiring for Data Scientist Project Manager jobs? Cities in Wisconsin with the most Data Scientist Project Manager job openings:
Infographic showing various Data Scientist Project Manager job openings in Wisconsin as of June 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, and 3% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution.

Full-time

Posted 23 days ago


Generac Power Systems rating

7.0

Company rating: 7.0 out of 10

Based on 64 frontline employees who took The Breakroom Quiz

289th of 418 rated machine equipment manufacturers


Job description

We are Generac, a leading energy technology company committed to powering a smarter world.

Over the 60 plus years of Generac's history, we've been dedicated to energy innovation. From creating the home standby generator market category, to our current evolution into an energy technology solutions company, we continue to push new boundaries.

As a senior member of the team, you will have significant responsibility and influence in shaping its future direction. We are looking for someone that leads data science projects from start to finish, defining the problem, identifying opportunities building proofs of concept and implements them as a data product.

You should have deep expertise data science, machine learning and statistical analysis, and the ability to scope out project requirements, time estimates, and resources needed. You should have excellent business and interpersonal skills to be able to work with business owners to understand data requirements, and to build highly scalable systems.

Successful candidates will have strong engineering skills and communication, as well as a belief that data driven processes lead to great products. You will need to have a passion for quality and an ability to understand complex systems.

Essential Duties:

  • We are looking for someone that leads data science projects from start to finish, defining the problem, identifying opportunities building proofs of concept and implements them as a data product.
  • Interact with different teams (Product, Data Platform, Frontend, etc.) to reach common ground and strive for win-win scenarios.
  • Keep updated with the state-of-the-art algorithms and techniques on the field and evaluate them in our business context.
  • Tell engaging data stories for both technical and non-technical audiences.
  • Transform business problems and opportunities into data product solutions.
  • Act as a mentor to junior data scientist.
  • Review pull requests from fellow team members.
  • Evaluate project ideas and provide technology input, prescribing appropriate application solutions, which balance business requirements with Generac's technology standards to arrive at the optimal solution.
  • Write user and technical specifications in line with business needs.

Basic Qualifications:

  • Bachelor's Degree in Computer Science, Math, Physics, Engineering, Statistics or related field,
  • 2+ years of experience post-grad in a Data Science / Machine Learning position.
  • Professional experience with Python.
  • Experience with SQL.
  • Experience with version control (GitHub or similar) in a team environment.
  • Demonstrated experience applying machine learning and data mining techniques.

Preferred Qualifications:

  • Master's and/or PhD are a strong plus
  • Experience in agentic AI across organization
  • Experience in cloud environments (AWS / Azure) are a strong plus

Knowledge, Skills, and Abilities:

  • Strong communication skills and commitment to teamwork
  • Sharp analytical abilities and proven design skills
  • Strong sense of ownership, urgency, and drive
  • Proven leadership abilities in an engineering environment in driving operational excellence and best practices.

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 occasionally lift up to 25 - 50 pounds. Specific conditions of this job are typical of frequent and continuous computer-based work requiring periods of sitting, close vision and 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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