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Data Science Engineer Jobs in Madison, WI (NOW HIRING)

SynergisticIT

Junior Software Engineer

Madison, WI

For data science/machine learning positions required skills bachelors degree or masters degree in ... computer engineering, electrical engineering, information systems, IT project work on the ...

Accuray

Motion Control Engineer

Madison, WI

Bachelor's degree in computer science, Software Engineering, Data Science, Engineering Physics, Mechanical Engineering, Mechatronics, or a closely related technical field. * At least 4years of ...

Wisconsin

Data Engineer

Madison, WI

$50K/yr

Data Engineer I Job Summary: About Us: The Institute on Aging is a research unit whose mission is ... Implements data analysis steps in collaboration with data scientists, statisticians, and/or other ...

University of Wisconsin-Madison

Data Engineer

Madison, WI · On-site

$50K/yr

Data Engineer I Job Summary: About Us: The Institute on Aging is a research unit whose mission is ... Implements data analysis steps in collaboration with data scientists, statisticians, and/or other ...

University of Wisconsin-Madison

Data Engineer

Madison, WI · On-site

$50K/yr

Data Engineer I Job Summary: About Us: The Institute on Aging is a research unit whose mission is ... Implements data analysis steps in collaboration with data scientists, statisticians, and/or other ...

Springs Window Fashions

Senior AI Engineer

Middleton, WI

$107K - $147K/yr

Required * Bachelor's degree in Computer Science, Information Technology, Data Science, Engineering, or a related field. * Advanced degree in Artificial Intelligence, Machine Learning, or Data ...

Springs Window Fashions

Senior AI Engineer

Middleton, WI · On-site

$107K - $147K/yr

Bachelor's degree in Computer Science, Information Technology, Data Science, Engineering, or a related field. * Advanced degree in Artificial Intelligence, Machine Learning, or Data Science preferred ...

Springs Window Fashions

Senior AI Engineer

Middleton, WI · On-site

$107K - $147K/yr

Bachelor's degree in Computer Science, Information Technology, Data Science, Engineering, or a related field. * Advanced degree in Artificial Intelligence, Machine Learning, or Data Science preferred ...

The Weather Channel

Senior Data Scientist

Madison, WI · On-site

You will work on a skilled team of passionate data scientists and meteorologists. Examples of ... Programming capabilities including C++, Java, Python is a plus but not necessary. Additional ...

The Weather Channel

Senior Data Scientist

Madison, WI · On-site

You will work on a skilled team of passionate data scientists and meteorologists. Examples of ... Programming capabilities including C++, Java, Python is a plus but not necessary. Additional ...

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Showing results 1-20

All JobsData Science Engineer JobsData Science Engineer Jobs in Madison, WI

Data Science Engineer information

See Madison, WI salary details

$44.8K

$130.7K

$178.9K

How much do data science engineer jobs pay per year?

As of Jun 14, 2026, the average yearly pay for data science engineer in Madison, WI is $130,725.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,400.00 and $138,600.00 per year, depending on experience, location, and employer.

Is AI replacing data scientists?

AI is transforming the role of data science engineers by automating routine tasks and enabling more advanced analysis, but it does not replace the need for skilled professionals who interpret data, develop models, and ensure ethical use. Data scientists and data science engineers are increasingly working alongside AI tools to enhance decision-making and innovation. The demand for expertise in programming, statistical analysis, and machine learning remains strong in the industry.

What are the key skills and qualifications needed to thrive in the Data Science Engineer position, and why are they important?

A Data Science Engineer should have a strong background in statistics, machine learning, programming (typically Python or R), and data engineering, often supported by a degree in computer science, engineering, or a related field. Familiarity with data processing frameworks (like Spark or Hadoop), cloud platforms (AWS, GCP, or Azure), and certifications in data science or cloud technology are highly valued. Excellent problem-solving skills, communication abilities, and collaboration are essential soft skills for working effectively in cross-functional teams. These competencies enable Data Science Engineers to build scalable data solutions, deliver actionable insights, and drive business impact.

What are the typical daily responsibilities of a Data Science Engineer?

Data Science Engineers typically spend their days designing and building data pipelines, preparing and cleaning large datasets, and developing machine learning models to solve business problems. They work closely with data scientists, software engineers, and business stakeholders to translate requirements into scalable technical solutions. Responsibilities also include deploying models to production, monitoring their performance, and iterating on solutions based on feedback. This role offers a dynamic mix of coding, data analysis, and teamwork, making each day varied and intellectually engaging.

Is 40 too late for data science?

Data Science Engineers can enter the field at any age, as success depends on skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant knowledge in programming, statistics, and tools like Python or R. Age is less important than demonstrated expertise and the ability to adapt to evolving technologies.

What is the 80 20 rule in data science?

The 80/20 rule in data science suggests that roughly 80% of the results come from 20% of the efforts or features. Data scientists often use this principle to focus on the most impactful variables, optimize models, and prioritize tasks for efficiency.

What is a Data Science Engineer job?

A Data Science Engineer is a professional who bridges the gap between data science and software engineering. They focus on designing, building, and maintaining scalable data pipelines, infrastructure, and machine learning models for production use. Their role involves data preprocessing, model deployment, performance optimization, and integrating AI solutions into applications. They work closely with data scientists, software engineers, and DevOps teams to ensure efficient data workflows.

What does a data science engineer do?

A data science engineer designs, develops, and maintains data pipelines and infrastructure to support data analysis and machine learning models. They work with large datasets, use programming languages like Python or Scala, and often collaborate with data scientists and software engineers to implement scalable data solutions.
What are the most commonly searched types of Data Science Engineer jobs in Madison, WI? The most popular types of Data Science Engineer jobs in Madison, WI are:
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Data Science Engineer jobs near you
Infographic showing various Data Science Engineer job openings in Madison, WI as of June 2026, with employment types broken down into 1% As Needed, 87% Full Time, 10% Part Time, and 2% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $130,725 per year, or $62.8 per hour.
Executive Director, AI and Enterprise Data Management

Executive Director, AI and Enterprise Data Management

Arrowhead Pharmaceuticals

Madison, WI • On-site

Full-time

Posted 22 days ago

Job description

Job Summary:
Arrowhead Pharmaceuticals is a commercial stage biopharmaceutical company focused on developing innovative drugs using RNA interference technology. The Executive Director of AI and Enterprise Data Management will lead the strategy and deployment of AI and data capabilities across the organization, enhancing operational efficiency and ensuring compliance with regulations.
Responsibilities:
• Define and execute a unified enterprise data and AI strategy aligned with company growth and R&D and commercialization goals
• Identify high-impact AI and data opportunities across all functions (R&D, Clinical, CMC, Manufacturing, G&A and etc.)
• Drive executive alignment on AI and data strategy, including opportunities, risks, and investment priorities
• Lead the design and implementation of an enterprise data platform enabling data integration across R&D, CMC, Clinical, and commercial domains
• Establish scalable data architecture to support real-time pipelines, advanced analytics, machine learning, agentic AI workflows, and AI-driven insights
• Enable interoperability and data sharing across previously siloed systems
• Define and own the enterprise AI acceptable-use policy, responsible AI framework, and guardrails for LLM deployment in regulated (GxP) workflows
• Ensure alignment with emerging regulatory guidance on AI/ML (FDA AI framework, NIST AI RMF, ISO 42001) and maintain audit-ready documentation for AI systems in regulated contexts
• Establish AI model lifecycle governance including validation, performance monitoring (LLMOps), and deprecation procedures
• Partner with Legal, Compliance, and Information Security to manage AI vendor risk and data privacy obligations
• Establish enterprise data governance frameworks including ownership, stewardship, data classification, quality standards, and lifecycle management
• Ensure compliance with regulatory requirements including GMP, GLP, GCP, SOX and data integrity standards
• Partner with Information Security to implement robust data protection, privacy, and AI governance guardrails
• Partner with IS and business function leaders to identify opportunities for data integration and AI-driven value creation
• Act as a bridge between technical and non-technical stakeholders to ensure adoption and impact
• Partner with business and IS leaders to prioritize, design, and deploy AI solutions that improve decision-making and operational efficiency
• Oversee development and scaling of AI agents and technology across functions such as Commercial, Finance, HR, and Legal
• Manage strategic relationships with AI vendors and development partners, including contracting, performance oversight, and alignment to enterprise standards
• Ensure all AI tools and vendors comply with security, data governance, and regulatory requirements in partnership with Information Security and Legal
• Build and lead a high-performing, multidisciplinary team spanning data engineering, data science, AI/ML, and informatics
• Integrate and scale the existing digital workspace/agent experimentation team into a formal enterprise function
• Foster a culture of innovation, collaboration, and continuous learning
Qualifications:
Required:
• 12+ years of experience in data, analytics, AI/ML, or informatics leadership roles
• Bachelor’s degree in Computer Science, Data Science, Engineering, Life Sciences, or a related field.
• Proven experience building and scaling enterprise data platforms and AI capabilities
• Experience in life sciences, biotechnology, pharmaceutical industry, or technology industry
• Demonstrated success operating in regulated environments
• Experience supporting commercial-stage organizations or scaling companies
• Deep understanding of modern data architectures, cloud platforms, and AI/ML technologies
• Strong business acumen with ability to translate strategy into execution
• Experience leading cross-functional transformation initiatives
• Ability to balance innovation with risk management and compliance
Preferred:
• Advanced Degree in Data Science, Engineering, Life Sciences or Business.
• Pharmaceutical industry experience
Company:
Arrowhead Pharmaceuticals is a biotechnology company that focuses on the development of medicine to treat diseases with a genetic origin. Founded in 1989, the company is headquartered in Pasadena, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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