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Director Of Data Science Jobs in Wisconsin (NOW HIRING)

Madison, WI Full Time (Direct Hire) • 5+ Years of total experience and 2-4 years of in-depth and superlative experience in Data Science. • Experience in Statistical modeling. • Candidate will ...

Data Scientist II/III

Madison, WI · On-site

$95 - $130/hr

... of reproducible research methodologies and analysis workflows * Independently identifies and implements appropriate data science techniques to find data patterns and answer research questions chosen ...

... of Exact Sciences, bringing together market-leading cancer screening tests with an emerging ... As the Director, Data Engineering , you'll serve as Cancer Diagnostics' senior data executive ...

New

... of Exact Sciences, bringing together market-leading cancer screening tests with an emerging ... As the Director, Data Engineering , you'll serve as Cancer Diagnostics' senior data executive ...

New

Department : Enterprise Analytics and Data Science * Reports to: Vice President, Enterprise ... Responsible for the daily management of data and analytics solutions development and adopts best ...

Identify and drive continuous improvement of key business metrics within the balanced team * Remain current on the latest trends and developments in data science and technology through self-learning ...

Promote consistent use of well-managed, reliable data sources across business units Advanced Analytics Support (10%) * Contribute to foundation work that supports the expansion of data science and ...

Showing results 41-60

Director Of Data Science information

See Wisconsin salary details

$54.5K

$156.3K

$246.3K

How much do director of data science jobs pay per year?

As of Aug 23, 2026, the average yearly pay for director of data science in Wisconsin is $156,322.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,000.00 and $191,300.00 per year, depending on experience, location, and employer.

What are some common challenges faced by a director of data science when leading cross-functional teams?

As a Director of Data Science, one of the key challenges is aligning the goals of data science teams with those of product, engineering, and business stakeholders. This often involves translating complex technical findings into actionable insights that non-technical colleagues can understand and use. Additionally, managing resource allocation and prioritizing projects across multiple departments can be demanding, especially in fast-paced environments. Building a collaborative culture and fostering open communication are crucial for overcoming these challenges and ensuring data-driven strategies deliver business value.

What are the key skills and qualifications needed to thrive as a director of data science, and why are they important?

A Director of Data Science needs advanced expertise in statistical analysis, machine learning, and data strategy, typically supported by a graduate degree in a quantitative field and significant industry experience. Familiarity with big data platforms (e.g., Hadoop, Spark), programming languages (Python, R), and cloud-based analytics tools, as well as experience managing data science teams, is essential. Strong leadership, communication, and business acumen are key soft skills for aligning technical work with organizational goals and influencing stakeholders. These skills are crucial for driving data-driven decision-making and maximizing the strategic impact of data science initiatives within the organization.

What is the difference between Director Of Data Science vs Data Scientist?

AspectDirector Of Data ScienceData Scientist
Required CredentialsAdvanced degrees (Master's or PhD), leadership experienceBachelor's or Master's in Data Science, Computer Science, or related fields
Work EnvironmentStrategic planning, team management, cross-department collaborationData analysis, model development, coding, and experimentation
Employer & Industry UsageTech companies, finance, healthcare, large enterprisesStartups, tech firms, research institutions, various industries

The main difference between a Director Of Data Science and a Data Scientist lies in their scope of responsibilities. The Director oversees strategic initiatives, manages teams, and aligns data projects with business goals, while Data Scientists focus on analyzing data, building models, and deriving insights. Both roles require strong technical skills, but the Director's role emphasizes leadership and strategic planning.

What does a director of data science do?

A director of data science oversees data science teams, develops strategies for data analysis and modeling, and ensures the implementation of data-driven solutions to support business goals. They often manage projects, collaborate with other departments, and have expertise in statistical methods, machine learning, and data management tools. Strong leadership, communication skills, and experience with programming languages like Python or R are essential for this role.

What are the most commonly searched types of Of Data Science jobs in Wisconsin?

The most popular types of Of Data Science jobs in Wisconsin are:

What cities in Wisconsin are hiring for Director Of Data Science jobs?

Cities in Wisconsin with the most Director Of Data Science job openings:

Infographic showing various Director Of Data Science job openings in Wisconsin as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $156,322 per year, or $75.2 per hour.

Data Scientist

Innovizant LLC

Madison, WI • On-site

Full-time

Re-posted 15 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