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Data Science Engineer Jobs in Wisconsin (NOW HIRING)

Newance

Senior Data Scientist

Green Bay, WI · On-site

As a member of our Data Science team, you will play a crucial role in leveraging, building and ... Data engineering concepts * Optimization model methodologies * Forecasting model development and ...

Deloitte

Senior AI Engineer - SFL Scientific

Milwaukee, WI · On-site

$102K - $141K/yr

Required : • Bachelor's degree in a STEM field (Computer Science, Engineering, Physics, etc.) or equivalent experience • 4+ years of experience working in data engineering, data science, software ...

SynergisticIT

Entry Level Data Analyst

Kenosha, WI · On-site

... Data Scientists. We welcome candidates with all visas and citizens to apply ... Recent Computer science/Engineering/Mathematics/Statistics or Science graduates looking to make ...

Deloitte

AI Engineer - SFL Scientific

Milwaukee, WI · On-site

Leverage advanced technical skills in modern data architecture, data science engineering, data transformation, and management of structured and unstructured data sources using cloud computing or on ...

Amcor

R&D Senior Manager - Data Science

Neenah, WI · On-site

MS or PhD in Data Science, Engineering, or a related field * 10+ years of experience in data science, analytics, or R&D digital transformation * 5+ years of leadership experience managing teams or ...

Amcor plc

R&D Senior Manager - Data Science

Neenah, WI · On-site

MS or PhD in Data Science, Engineering, or a related field * 10+ years of experience in data science, analytics, or R&D digital transformation * 5+ years of leadership experience managing teams or ...

CTech Manufacturing

Data Engineer

Schofield, WI · On-site

$114K - $137K/yr

Associate's degree or higher in Computer Science, Data Science, Information Systems, or a related field 0-3 years of professional experience in data engineering, business intelligence, analytics, or ...

Deloitte

Senior AI Engineer - SFL Scientific

Milwaukee, WI · On-site

$103K - $141K/yr

Leverage advanced technical skills in modern data architecture, data science engineering, data transformation, and management of structured and unstructured data sources using cloud computing or on ...

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$44.9K

$130.9K

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How much do data science engineer jobs pay per year?

As of Jun 26, 2026, the average yearly pay for data science engineer in Wisconsin is $130,930.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,600.00 and $138,800.00 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 Wisconsin? The most popular types of Data Science Engineer jobs in Wisconsin are:
What are popular job titles related to Data Science Engineer jobs in Wisconsin? For Data Science Engineer jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Data Science Engineer jobs in Wisconsin look for? The top searched job categories for Data Science Engineer jobs in Wisconsin are:
What cities in Wisconsin are hiring for Data Science Engineer jobs? Cities in Wisconsin with the most Data Science Engineer job openings:
Data Science Engineer jobs near you
Infographic showing various Data Science Engineer job openings in Wisconsin as of June 2026, with employment types broken down into 1% As Needed, 91% Full Time, 5% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $130,930 per year, or $62.9 per hour.

Senior Data Scientist

Newance

Green Bay, WI • On-site

Full-time

Posted 12 days ago

Job description

 POSITION SUMMARY
We are seeking a skilled and motivated Senior Data Scientist to join our dynamic and innovative Data Intelligence Organization. As a member of our Data Science team, you will play a crucial role in leveraging, building and developing analytical tools to solve complex business problems. You will also be expected to act as mentor to junior team members, growing their skillsets while working to advance your skillset and developing new solutions to add to the analytical tools available to the Data Science Team and the Data Intelligence Organization.
This role will work on-site in Green Bay with in office expectations Monday - Thursday and optional remote work Friday's as business needs allow.JOB RESPONSIBILITIES
Development:
  • The expectation is that this individual will join the team being
    • Expertly skilled in the following:
      • Understanding of core processes: data collection, cleansing, data models, data modeling and data visualization.
      • Understanding of the businesses for which Breakthrough provides solutions and products and how those solutions and products operate.
      • While maintaining company coding standards, demonstrate the ability to build solutions, solve problems and develop in the coding languages used at Breakthrough (SQL, R, Python).
    • Proficient in executing of the following:
      • Advanced statistical modeling techniques (ML/AI)
      • Data engineering concepts
      • Optimization model methodologies
      • Forecasting model development and management
      • Ability to deploy developed models into a production system.
  • This individual will be considered a mentor to junior members of the Data Science Team contributing to their professional growth.

Innovation
  • The Data Science Team is one of the teams at the forefront of innovation at Breakthrough. This individual will be expected to be a leader in the ideation that occurs within the team.
  • This individual will be involved in leading white boarding sessions with other Data Science team members and team members outside of the Data Science Team. They will be expected to generate new ideas, foster discussion and be a leader in the innovation process.
  • This individual will build innovative solutions such as simulations and proof-of-concepts that will be utilized for making key decisions by the business.
  • This individual will also take part in the direction of junior team members in the development of innovative solutions.
  • This individual will be expected to pay attention to industry trends and model development potential use cases to leverage new ideas at Breakthrough.

Execution
  • The responsibilities this individual also includes:
    • Building data sets that they will use to estimate statistical and analytical models to solve complex analytical problems like forecasting and optimizations.
    • Building data visualizations that communicate the results of the project to internal stakeholders.
    • Communicating and presenting outcomes to internal and external stakeholders including senior leadership.
    • Writing documentation that outlines the work done and reviewing more junior members' documentation
    • Using code repositories for version control of models built
  • This individual will be leading, assigning and managing the execution of projects and will not be a key contributor in all projects. This will involve:
    • Talking with project owners from outside the Data Intelligence Organization.
    • Presenting outcomes to leadership.

Collaboration:
  • This individual will need to have strong interpersonal skills with the ability to build rapport and establish credibility with stakeholders at all levels including senior leadership.
  • Working with all team members and lead in the improvement of development processes.
  • Embrace mentorship of junior team members and develop and execute training programs.
QUALIFICATIONS
Required:
  • Bachelor's or Master's degree in Business Administration, Economics, Statistics, Computer Science or a related field involving problem solving and critical thinking, or equivalent work experience.
  • 5+ years working in data science-specific roles, with demonstrated experience working in roles that require proficiency with data modeling, statistical modeling, model deployment, data management and SQL-based development.
  • Expert ability to develop effective data visualizations that are used by upper management in decision-making situations.
  • Expertise in multiple programming languages, frameworks, and technologies, specifically Python, SQL, R, and orchestrators (DBT, Vertex, Airflow etc.). BigQuery experience a plus.
  • Proficient understanding of database concepts and data modeling principles.
  • Demonstrated high-level business acumen with a supply chain/transportation background being preferred.
  • Excellent problem-solving skills and the ability to navigate complex analytical and data-related challenges.
  • Advanced analytical skills with an emphasis on attention to detail and being able to look at a problem from multiple angles and perspectives.
  • Strong communication skills, with the ability to articulate complex technical concepts to both technical and non-technical stakeholders.

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