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Behavioral Science Researcher Jobs in Tulsa, OK (NOW HIRING)

Deloitte

Lead AI and Data Science Engineer II

Tulsa, OK

$93K - $123K/yr

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

Varsity Tutors

College Political Science Tutor

Tulsa, OK · Remote

$18 - $40/hr

... research methods, constitutional law, and political behavior. Ability to explain separation of ... Familiar with political science curricula at introductory and upper-division levels and common ...

State of Oklahoma

Rehabilitation Technician

Tulsa, OK · On-site

$38K/yr

... researching and processing electronic case files and performing tasks related to general office ... a behavioral science or a closely related field and one year of experience in career counseling ...

State of Oklahoma

Rehabilitation Technician

Tulsa, OK · On-site

$38K/yr

... researching and processing electronic case files and performing tasks related to general office ... a behavioral science or a closely related field and one year of experience in career counseling ...

Varsity Tutors

Psychology Tutor

Tulsa, OK · Remote

$18 - $40/hr

Deep knowledge of research methods, biological bases of behavior, sensation and perception ... science to create personalized learning experiences. Through 1-on-1 Online Tutoring, students ...

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Showing results 1-20

All JobsBehavioral Science Researcher JobsBehavioral Science Researcher Jobs in Tulsa, OK

Behavioral Science Researcher information

See Tulsa, OK salary details

$27.4K

$103.3K

$150.2K

How much do behavioral science researcher jobs pay per year?

As of Aug 10, 2026, the average yearly pay for behavioral science researcher in Tulsa, OK is $103,304.00, according to ZipRecruiter salary data. Most workers in this role earn between $61,200.00 and $140,700.00 per year, depending on experience, location, and employer.

Is behavioral science researcher in high demand?

Behavioral science researchers are in growing demand across industries such as healthcare, marketing, and public policy, as organizations seek to understand and influence human behavior. The role often requires strong analytical skills, knowledge of research methods, and proficiency with data analysis tools, with job opportunities increasing as organizations prioritize evidence-based decision making.

What are some common challenges behavioral science researchers face when conducting field studies, and how can they address them?

Behavioral Science Researchers often encounter challenges such as participant recruitment, ensuring data validity, and controlling for external variables in field settings. Building rapport with communities and clearly communicating the study's purpose can help with recruitment. To maintain data quality, researchers should establish rigorous protocols and use validated measurement tools. Collaborating closely with interdisciplinary teams and local stakeholders can also help anticipate and mitigate logistical and ethical challenges.

What are the key skills and qualifications needed to thrive as a behavioral science researcher, and why are they important?

To thrive as a Behavioral Science Researcher, you need expertise in research design, statistical analysis, and a solid background in psychology or related fields, often supported by an advanced degree. Familiarity with statistical software like SPSS, R, or Python, as well as experience with survey tools and data collection platforms, is typically required. Strong critical thinking, communication skills, and attention to detail help researchers interpret findings and collaborate effectively. These competencies are essential for generating valid insights, ensuring rigorous research, and translating behavioral data into actionable recommendations.

What can I do with a behavioral science researcher degree?

A behavioral science researcher degree prepares individuals for roles in academia, government, or private sectors, focusing on analyzing human behavior to inform policy, marketing, or product development. Common positions include research analyst, data scientist, or behavioral consultant, often requiring skills in data analysis, experimental design, and familiarity with statistical tools. Graduates may also pursue further certifications or advanced degrees to expand career opportunities.

What does a behavioral science researcher do?

A Behavioral Science Researcher studies how people think, feel, and behave by using methods from psychology, sociology, and related fields. They design and conduct experiments or surveys, analyze data, and interpret findings to understand human behavior. Their work can inform policies, improve products or services, and address social issues. Behavioral Science Researchers often work in academic, government, healthcare, or corporate settings and collaborate with professionals from various disciplines.
What are popular job titles related to Behavioral Science Researcher jobs in Tulsa, OK? For Behavioral Science Researcher jobs in Tulsa, OK, the most frequently searched job titles are:
What job categories do people searching Behavioral Science Researcher jobs in Tulsa, OK look for? The top searched job categories for Behavioral Science Researcher jobs in Tulsa, OK are:
What cities near Tulsa, OK are hiring for Behavioral Science Researcher jobs? Cities near Tulsa, OK with the most Behavioral Science Researcher job openings:
Behavioral Science Researcher jobs near you
Infographic showing various Behavioral Science Researcher job openings in Tulsa, OK as of August 2026, with employment types broken down into 1% Internship, 1% As Needed, 76% Full Time, 19% Part Time, and 3% Contract. Highlights an 76% Physical, 4% Hybrid, and 20% Remote job distribution, with an average salary of $103,304 per year, or $49.7 per hour.

Lead AI and Data Science Engineer II

Deloitte

Tulsa, OK

$93K - $123K/yr

Full-time

Posted 11 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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