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Behavioral Data Science Jobs in Minnesota (NOW HIRING)

Phaedon, LLC

Senior Data Scientist

Minneapolis, MN · On-site

... behavior prediction, personalization/recommendation, anomaly detection) and bring proposals forward ... Bachelor's degree in data science, computer science, computer engineering, or related field AND 5+ ...

In Tandem

Product Data Scientist

Minneapolis, MN

$100K - $140K/yr

As our Product Data Scientist , you'll bring rigorous behavior analysis and predictive modeling to how our apps understand and serve our members -- partnering closely with Product and Finance to turn ...

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Behavioral Data Science information

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$23.3K

$104.3K

$194.3K

How much do behavioral data science jobs pay per year?

As of Aug 6, 2026, the average yearly pay for behavioral data science in Minnesota is $104,328.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,754.00 and $141,856.00 per year, depending on experience, location, and employer.

What can I do with a behavioral data science degree?

A behavioral data science degree prepares individuals for roles such as data analyst, behavioral scientist, or user experience researcher, focusing on analyzing human behavior through data. Graduates often work with statistical tools, programming languages like Python or R, and data visualization software to inform decision-making in marketing, product development, or healthcare. These roles typically require strong analytical skills and understanding of psychological or social science principles.

What does a behavioral data scientist do?

A behavioral data scientist analyzes data related to human behavior to identify patterns and insights that can inform decision-making. They use statistical methods, machine learning, and data visualization tools to interpret complex datasets and often work with psychology, marketing, or product teams to improve user engagement and outcomes.

What is behavioral data science?

A Behavioral Data Science job focuses on analyzing human behavior using data-driven techniques from psychology, economics, and machine learning. Professionals in this field work with large datasets to understand, predict, and influence decision-making patterns. They apply statistical models, AI, and behavioral theories to areas like marketing, finance, healthcare, and policy-making. The role typically involves data collection, analysis, and interpretation to optimize user experiences and business strategies.

What types of projects or problems do behavioral data scientists typically work on?

Behavioral Data Scientists often tackle projects that involve analyzing patterns in user behavior, identifying factors that drive engagement, or developing predictive models related to decision-making. They may work on optimizing customer experiences, evaluating the effectiveness of behavioral interventions, or supporting product teams with data-driven insights. The role frequently involves collaborating with psychologists, UX researchers, and business strategists to integrate behavioral data into broader company goals. This work requires both technical analysis and the ability to communicate findings to diverse stakeholders.

Is behavioral data science in high demand?

Behavioral data science is in high demand as organizations seek to understand human behavior through data analysis, machine learning, and statistical modeling. Professionals with skills in programming, data visualization, and behavioral psychology are especially sought after across industries such as marketing, healthcare, and finance.

What are the key skills and qualifications needed to thrive in behavioral data science, and why are they important?

To thrive as a Behavioral Data Scientist, you need expertise in behavioral science, statistics, and data analysis, typically backed by an advanced degree in psychology, data science, or a related field. Familiarity with tools like Python, R, SQL, and data visualization platforms, as well as certifications in data analytics, is highly valued. Strong critical thinking, communication, and collaboration skills help you interpret complex data patterns and translate them into actionable insights. These abilities are crucial for effectively analyzing human behavior data and driving organizational decision-making.

What are the most commonly searched types of Behavioral Data Science jobs in Minnesota? The most popular types of Behavioral Data Science jobs in Minnesota are:
What are popular job titles related to Behavioral Data Science jobs in Minnesota? For Behavioral Data Science jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Behavioral Data Science jobs in Minnesota look for? The top searched job categories for Behavioral Data Science jobs in Minnesota are:
What cities in Minnesota are hiring for Behavioral Data Science jobs? Cities in Minnesota with the most Behavioral Data Science job openings:
Behavioral Data Science jobs near you
Infographic showing various Behavioral Data Science job openings in Minnesota as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $104,328 per year, or $50.2 per hour.

Lead AI and Data Science Engineer II

Deloitte

Minneapolis, MN

$107K - $140K/yr

Other

Posted 7 days ago

Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

46th 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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