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Data Science Project Manager Jobs in Wisconsin (NOW HIRING)

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 ...

Forecasting model development, lifecycle management, and continuous improvement across demand ... projects in the Data Science portfolio-the work that requires the deepest technical judgment and ...

With $8.1 billion in revenue for 2025, Clayco specializes in the "art and science of building ... The Role We Want You For The Project Manager will be based on the construction project site. In ...

With $8.1 billion in revenue for 2025, Clayco specializes in the "art and science of building ... The Role We Want You For The Project Manager will be based on the construction project site. In ...

With $8.1 billion in revenue for 2025, Clayco specializes in the "art and science of building ... The Role We Want You For The Project Manager will be based on the construction project site. In ...

With $8.1 billion in revenue for 2025, Clayco specializes in the "art and science of building ... The Role We Want You For The Project Manager will be based on the construction project site. In ...

To learn more about playing for Team Amcor, visitwww.amcor.comILinkedInIGlassdoorIFacebook IYouTube The R&D Senior Manager - Data Science is a strategic leadership role responsible for advancing ...

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Data Science Project Manager information

See Wisconsin salary details

$16

$58

$81

How much do data science project manager jobs pay per hour?

As of Jul 2, 2026, the average hourly pay for data science project manager in Wisconsin is $58.05, according to ZipRecruiter salary data. Most workers in this role earn between $50.24 and $67.93 per hour, depending on experience, location, and employer.

What is the hottest job of the 21st century?

Data Science Project Managers are in high demand due to the rapid growth of data-driven decision-making across industries. They oversee data projects, coordinate teams, and require skills in analytics tools, project management, and communication. The role is considered one of the most sought-after careers in the 21st century for its impact and earning potential.

What is a Data Science Project Manager?

A Data Science Project Manager is a professional who oversees and coordinates data science projects from inception to completion. They act as a bridge between technical data science teams and business stakeholders, ensuring that project goals align with organizational objectives. Responsibilities include planning project timelines, managing resources, mitigating risks, and communicating progress. They also help define project requirements, monitor deliverables, and ensure that outcomes meet quality standards. Strong communication, analytical, and organizational skills are essential for this role.

Is 40 too late for data science?

For a Data Science 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 tools like Python or R and understanding business needs, regardless of age.

Can data scientists make $300k?

Data scientists can earn $300,000 or more annually, especially with extensive experience, advanced skills in machine learning and big data tools, and roles in high-paying industries or senior management positions. Achieving this level often requires a combination of technical expertise, certifications, and leadership responsibilities.

How does a Data Science Project Manager typically collaborate with data scientists and stakeholders throughout a project?

A Data Science Project Manager acts as a bridge between technical teams and business stakeholders, ensuring clear communication of goals, timelines, and deliverables. They facilitate regular meetings to discuss project progress, address any obstacles, and realign priorities as needed. By translating business requirements into actionable tasks for data scientists and providing updates to stakeholders, they help ensure that projects stay on track and deliver value. Effective collaboration often involves balancing technical feasibility with business needs, managing expectations, and fostering a cooperative team environment.

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

AspectData Science Project ManagerData Analyst
Required CredentialsOften requires a bachelor’s or master’s in data science, analytics, or related fields; project management certifications beneficialTypically holds a bachelor’s degree in statistics, mathematics, or related areas; certifications like Microsoft Excel or Tableau are common
Work EnvironmentLeads data science projects, collaborates with data scientists, engineers, and stakeholdersAnalyzes data sets, creates reports, visualizations, and supports decision-making
Employer & Industry UsageUsed in tech, finance, healthcare, and consulting firms managing data science initiativesFound across industries for data reporting, business intelligence, and operational analysis

In summary, a Data Science Project Manager oversees data science projects and manages teams, requiring project management skills and relevant certifications. A Data Analyst focuses on analyzing data and creating reports, with a more technical and analytical role. Both roles are essential in data-driven organizations but differ in scope and responsibilities.

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

To thrive as a Data Science Project Manager, you need a solid understanding of data science methodologies, project management principles, and usually a degree in computer science, statistics, or a related field. Familiarity with analytics tools (such as Python, R, SQL), project management software (like Jira or Trello), and certifications such as PMP or Agile/Scrum are often required. Strong leadership, communication, and problem-solving skills set top performers apart by enabling effective team coordination and stakeholder management. These competencies ensure projects are delivered on time, within scope, and generate actionable insights that drive business value.

Can a data scientist become a project manager?

Yes, a data scientist can become a project manager by developing skills in leadership, communication, and project planning. Gaining experience in managing teams, understanding project workflows, and obtaining certifications like PMP can facilitate this transition.
What are popular job titles related to Data Science Project Manager jobs in Wisconsin? For Data Science Project Manager jobs in Wisconsin, the most frequently searched job titles are:
Data Scientist

Full-time

Posted 21 days ago


Job description

Company Description

Innovizant LLC (headquartered in Chicago, USA) is a leading-edge, global IT Services organization with Sales and delivery offices in Asia. Innovizant LLC, is a Full-service IT provider, focused on delivering Innovative and value driven business analytical solutions leveraging data science, data engineering and decision science to provide winning actionable insights assisting our financial services clients banking, Insurance and credit union business in achieve their business goals.
Innovizant made up of exceptional data scientists and domain experts with a great experience in Our financial services industry solutions include Credit Risk insights, Customer Churn analysis, Customer segmentation, Fraud detection, Asset and Liability analysis, channel optimization analytics, Financial Advisor Network Analytics and product bundling analytics.

Some of our sur accelerators and solution frameworks assist our clients including FIN-CDO (which provided pre-delivered data strategies for the office of Chief Data Officer), BASEL-PRO (for achieving compliance with industry requirements of Basel-BCBS239,) and SmartCECL (Risk mitigation strategies by predicting default and loss given a default)

With data becoming the new 'oxygen' of businesses, many data science consulting firms have evolved in recent times, and they are also contributing the best of their solutions to the modern-day clients. It means today; you can easily find a solution for data sciences. 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 events.
Many organizations have ended up spending a significant chunk of their analytics budget in some implementing data sciences solution - with minimal to no returns.

Job Description

Role: Data Scientist

Location: Madison, WI

Full Time (Direct Hire)

Job description

         5+ Years of total experience and 2-4 years of in-depth and superlative experience in Data Science.

         Experience in Statistical modeling.

         Candidate will be helping the client to lead this process or improve upon the program.

         Extremely proficient in Data Analysis, data wrangling, model development, software development, A/B Testing, Back Testing.

         Extremely efficient in Python and R.

         Extremely efficient in identifying right analytics model methods and using them. Gradient Boosting, Decision Tree, Regression - are absolutely must.

         Exposure to Insurance (especially consumer Insurance/Retail Insurance) is a minor edge.

         MS in AI/Data Science would also be a plus.

Qualifications

Data Science, Analysis, Python, R, Statistical Modeling, Machine Learning

Additional Information

Thanks & Regards,

Aditya Prakash | Resource Manager | Innovizant LLC

Phone : 630-685-1260

aditya.prakash(AT)innovizant(DOT)com