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Behavioral Science Jobs in Wisconsin (NOW HIRING)

Deloitte

Lead AI and Data Science Engineer II

Milwaukee, WI · On-site

$101K - $133K/yr

The team combines behavioral science, organizational research, advanced analytics, and artificial intelligence (AI) to address leadership questions, improve decision-making, and create scalable ...

Baylor College of Medicine

WI · On-site

$150 - $200/hr

Title Psychiatry & Behavioral Sciences - Psychiatry Research (Associate Professor) Summary Baylor ... science institution located within the world's largest medical center in Houston, Texas. It is ...

New

Rawhide Youth Services

Case Manager

New London, WI · On-site

Either a bachelor's degree in a social or behavioral science field with two years of related work experience, or a master's degree in a social or behavioral science field * Strong interpersonal ...

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All JobsBehavioral Science JobsBehavioral Science Jobs in Wisconsin

Behavioral Science information

See Wisconsin salary details

$24.7K

$48.8K

$79.7K

How much do behavioral science jobs pay per year?

As of Aug 7, 2026, the average yearly pay for behavioral science in Wisconsin is $48,843.00, according to ZipRecruiter salary data. Most workers in this role earn between $38,900.00 and $52,500.00 per year, depending on experience, location, and employer.

Is behavioral science in high demand?

Behavioral science is increasingly in demand across industries such as healthcare, marketing, and public policy, as organizations seek to understand and influence human behavior. Professionals with skills in data analysis, research methods, and behavioral theories are valued, and the field is expected to grow as organizations prioritize evidence-based decision making.

What can you do with a behavioral science degree?

A behavioral science degree prepares individuals for roles such as behavioral analyst, research coordinator, or user experience researcher, focusing on understanding human behavior to improve products, services, or policies. Graduates often work in healthcare, marketing, public policy, or consulting, utilizing skills in data analysis, psychology, and research methods.

How do behavioral science professionals typically collaborate with other departments within an organization?

Behavioral Science professionals often work closely with teams such as marketing, human resources, product development, and data analytics to apply behavioral insights to real-world challenges. Collaboration can include designing experiments, interpreting data, and providing recommendations to improve user experiences or organizational outcomes. Regular meetings and cross-functional projects are common, requiring strong communication skills and the ability to translate complex behavioral concepts into actionable strategies. This collaborative environment fosters learning and provides opportunities for professionals to see the tangible impact of their work.

What is behavioral science?

Behavioral science is the study of how people make decisions, act, and interact with others. It draws from disciplines like psychology, sociology, and anthropology to understand human behavior and motivation. Professionals in this field use research and data analysis to understand patterns of behavior, which can help improve outcomes in areas such as health, business, education, and policy. Behavioral scientists often work to design interventions or policies that encourage positive behavioral changes.

What are the key skills and qualifications needed to thrive as a behavioral scientist?

To thrive as a Behavioral Scientist, you need a solid grounding in psychology, research methods, data analysis, and typically an advanced degree such as a master's or Ph.D. in behavioral science or a related field. Familiarity with statistical software like SPSS, R, or Python, and experience in survey design tools are commonly required. Strong critical thinking, communication skills, and the ability to collaborate across disciplines help Behavioral Scientists excel. These skills enable professionals to design effective studies, analyze human behavior accurately, and translate findings into actionable insights for organizations or policy.

What is the difference between Behavioral Science vs Data Analyst?

AspectBehavioral ScienceData Analyst
Required CredentialsDegree in psychology, sociology, or related fields; knowledge of research methodsDegree in statistics, mathematics, or related fields; proficiency in data analysis tools
Work EnvironmentResearch settings, consulting firms, or corporate teams focusing on human behaviorBusiness, finance, healthcare, or tech companies analyzing data trends
Employer & Industry UsageUsed by organizations aiming to understand and influence human behaviorUsed by organizations to interpret data and inform decision-making

While both roles involve analyzing information, Behavioral Scientists focus on understanding human behavior through research and psychological principles, whereas Data Analysts interpret data sets to support business decisions. Both careers require analytical skills but differ in their focus and application.

What jobs do behavioral scientists do?

Behavioral scientists analyze human behavior to develop insights that improve decision-making, policies, and products. They work in areas such as healthcare, marketing, public policy, and organizational development, often using research methods like experiments and data analysis. Their roles may include consulting, designing interventions, and conducting behavioral research to influence positive outcomes.
What are the most commonly searched types of Behavioral Science jobs in Wisconsin? The most popular types of Behavioral Science jobs in Wisconsin are:
What are popular job titles related to Behavioral Science jobs in Wisconsin? For Behavioral Science jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Behavioral Science jobs in Wisconsin look for? The top searched job categories for Behavioral Science jobs in Wisconsin are:
What cities in Wisconsin are hiring for Behavioral Science jobs? Cities in Wisconsin with the most Behavioral Science job openings:
Behavioral Science jobs near you
Infographic showing various Behavioral Science job openings in Wisconsin as of August 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 21% Part Time, and 3% Contract. Highlights an 77% Physical, 3% Hybrid, and 20% Remote job distribution, with an average salary of $48,843 per year, or $23.5 per hour.

Lead AI and Data Science Engineer II

Deloitte

Milwaukee, WI • On-site

$101K - $133K/yr

Other

Posted 8 days ago

Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

45th of 150 rated financial services

Job description

Lead AI and Data Science Engineer II

Drive the design and delivery of advanced analytics, artificial intelligence (AI), and generative artificial intelligence (GenAI) solutions that inform Talent strategy and workforce decisions. In this role, you will lead complex data science work that combines research design, statistical analysis, machine learning, and application development to solve high-priority people challenges. You will also partner with business, Talent, and technology stakeholders to translate workforce data into actionable insights, tools, and recommendations.

Recruiting for this role ends on August 10, 2026.

Work You'll Do

In this role, you will lead the data science dimension of that work, shaping research design, analytical methodology, and solution development while helping develop junior data scientists across the full analytics lifecycle.

Strategy & Stakeholder Partnership

  • Partner with the Advanced Analytics & AI leader to help shape and execute the People Analytics portfolio, using data-driven insights to inform Talent strategy, establish priorities, and manage multiple initiatives.
  • Collaborate with stakeholders across Talent, business leadership, and ITS to define business needs, identify analytics opportunities, communicate complex technical concepts, and advise on the benefits and limitations of automation and artificial intelligence (AI).
  • Develop and drive strategy to understand and improve data quality across relevant Talent data assets.

Analytics & Data Science

  • Design and structure analytical work, including research design, project planning, and use case development, and apply advanced statistical and machine learning methods to generate rigorous, actionable insights.
  • Perform analytics in cloud-based environments, support the development of clear leadership-ready presentations, and stay current on developments in data science, behavioral science, and adjacent disciplines.

Software & Data Engineering

  • Develop full-stack, web-based data and generative artificial intelligence (GenAI) applications that improve Talent reporting and business operations.
  • Partner with data engineering teams on pipeline architecture and infrastructure, using knowledge of extract, transform, load (ETL), version control, and continuous integration and continuous delivery (CI/CD) concepts to inform technical decisions.

People Leadership

  • Mentor junior and mid-level data scientists across the analytics lifecycle, from problem framing and data collection through analysis and synthesis of findings.
  • Provide structure and oversight for analytically complex projects, while assessing talent, delivering developmental feedback, and contributing to a high-performing analytics team.

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • 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 meet deadlines
  • Ability to mentor and provide clear guidance to others

The team

The Talent Experience & Engagement, People Analytics - Advanced Analytics & AI team helps the firm make informed people and business decisions by translating workforce data into actionable insights, tools, and strategies. The team combines behavioral science, organizational research, advanced analytics, and artificial intelligence (AI) to address leadership questions, improve decision-making, and create scalable solutions with measurable impact.

The work is delivered through two connected capabilities. Organizational research and storytelling ground analyses in rigorous social science and clear, decision-oriented narratives. Data science applies statistical analysis, machine learning, and AI to identify meaningful patterns in workforce data, build data and generative artificial intelligence (GenAI) applications, and partner with Talent data engineering teams on pipelines and infrastructure.

Qualifications

Required:

  • Graduate degree in Applied Statistics, Computer Science, Life Sciences, Industrial-Organizational Psychology, Organizational Behavior, Sociology, Economics, Anthropology, or another quantitative discipline
  • 6+ years of experience in data science, analytics, or applied research
  • Experience using Python and Structured Query Language (SQL), with working knowledge of JavaScript, TypeScript, HyperText Markup Language (HTML), and Cascading Style Sheets (CSS)
  • Experience applying multivariate statistics and machine learning methods, including regression, structural equation modeling, factor analysis, decision trees, clustering, and dimension reduction, in Apache Spark or Databricks environments
  • Experience developing artificial intelligence (AI) or generative artificial intelligence (GenAI) applications and working with extract, transform, load (ETL), pipeline design, and orchestration concepts
  • Demonstrated experience leading AI strategy and enabling adoption of AI or data engineering tools within a complex organizational environment
  • Mentorship of junior and mid-level analysts, providing guidance across the analytics lifecycle from conception through data mining/analysis and synthesis of results
  • Ability to travel 0-10%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.

Preferred:

  • Doctor of Philosophy (PhD) in Applied Statistics, Computer Science, Life Sciences, Industrial-Organizational Psychology, Organizational Behavior, Sociology, Economics, Anthropology, or another quantitative discipline
  • Experience in a professional services organization or large matrixed organization
  • Experience designing and building end-to-end data pipelines for reporting and analytics
  • Experience applying behavioral science frameworks to interpret workforce data and generate insight - not solely technical or statistical proficiency
  • Experience with talent systems such as OneModel or SAP

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $118700 to $218600.

Qualifications:

Lead AI and Data Science Engineer II

Drive the design and delivery of advanced analytics, artificial intelligence (AI), and generative artificial intelligence (GenAI) solutions that inform Talent strategy and workforce decisions. In this role, you will lead complex data science work that combines research design, statistical analysis, machine learning, and application development to solve high-priority people challenges. You will also partner with business, Talent, and technology stakeholders to translate workforce data into actionable insights, tools, and recommendations.

Recruiting for this role ends on August 10, 2026.

Work You'll Do

In this role, you will lead the data science dimension of that work, shaping research design, analytical methodology, and solution development while helping develop junior data scientists across the full analytics lifecycle.

Strategy & Stakeholder Partnership

  • Partner with the Advanced Analytics & AI leader to help shape and execute the People Analytics portfolio, using data-driven insights to inform Talent strategy, establish priorities, and manage multiple initiatives.
  • Collaborate with stakeholders across Talent, business leadership, and ITS to define business needs, identify analytics opportunities, communicate complex technical concepts, and advise on the benefits and limitations of automation and artificial intelligence (AI).
  • Develop and drive strategy to understand and improve data quality across relevant Talent data assets.

Analytics & Data Science

  • Design and structure analytical work, including research design, project planning, and use case development, and apply advanced statistical and machine learning methods to generate rigorous, actionable insights.
  • Perform analytics in cloud-based environments, support the development of clear leadership-ready presentations, and stay current on developments in data science, behavioral science, and adjacent disciplines.

Software & Data Engineering

  • Develop full-stack, web-based data and generative artificial intelligence (GenAI) applications that improve Talent reporting and business operations.
  • Partner with data engineering teams on pipeline architecture and infrastructure, using knowledge of extract, transform, load (ETL), version control, and continuous integration and continuous delivery (CI/CD) concepts to inform technical decisions.

People Leadership

  • Mentor junior and mid-level data scientists across the analytics lifecycle, from problem framing and data collection through analysis and synthesis of findings.
  • Provide structure and oversight for analytically complex projects, while assessing talent, delivering developmental feedback, and contributing to a high-performing analytics team.

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • 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 meet deadlines
  • Ability to mentor and provide clear guidance to others

The team

The Talent Experience & Engagement, People Analytics - Advanced Analytics & AI team helps the firm make informed people and business decisions by translating workforce data into actionable insights, tools, and strategies. The team combines behavioral science, organizational research, advanced analytics, and artificial intelligence (AI) to address leadership questions, improve decision-making, and create scalable solutions with measurable impact.

The work is delivered through two connected capabilities. Organizational research and storytelling ground analyses in rigorous social science and clear, decision-oriented narratives. Data science applies statistical analysis, machine learning, and AI to identify meaningful patterns in workforce data, build data and generative artificial intelligence (GenAI) applications, and partner with Talent data engineering teams on pipelines and infrastructure.

Qualifications

Required:

  • Graduate degree in Applied Statistics, Computer Science, Life Sciences, Industrial-Organizational Psychology, Organizational Behavior, Sociology, Economics, Anthropology, or another quantitative discipline
  • 6+ years of experience in data science, analytics, or applied research
  • Experience using Python and Structured Query Language (SQL), with working knowledge of JavaScript, TypeScript, HyperText Markup Language (HTML), and Cascading Style Sheets (CSS)
  • Experience applying multivariate statistics and machine learning methods, including regression, structural equation modeling, factor analysis, decision trees, clustering, and dimension reduction, in Apache Spark or Databricks environments
  • Experience developing artificial intelligence (AI) or generative artificial intelligence (GenAI) applications and working with extract, transform, load (ETL), pipeline design, and orchestration concepts
  • Demonstrated experience leading AI strategy and enabling adoption of AI or data engineering tools within a complex organizational environment
  • Mentorship of junior and mid-level analysts, providing guidance across the analytics lifecycle from conception through data mining/analysis and synthesis of results
  • Ability to travel 0-10%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.

Preferred:

  • Doctor of Philosophy (PhD) in Applied Statistics, Computer Science, Life Sciences, Industrial-Organizational Psychology, Organizational Behavior, Sociology, Economics, Anthropology, or another quantitative discipline
  • Experience in a professional services organization or large matrixed organization
  • Experience designing and building end-to-end data pipelines for reporting and analytics
  • Experience applying behavioral science frameworks to interpret workforce data and generate insight - not solely technical or statistical proficiency
  • Experience with talent systems such as OneModel or SAP

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to ski...

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