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How much do data scientist psychology jobs pay per year?

As of Sep 4, 2026, the average yearly pay for data scientist psychology in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is a data scientist psychology?

Data Scientist Psychologists are professionals who combine expertise in psychology with advanced data analysis skills. They design and conduct studies, analyze complex psychological data, and use statistical and machine learning techniques to uncover patterns in human behavior. Their work often supports research, clinical decision-making, or the development of mental health technologies. By leveraging data science, they help translate psychological theories into actionable insights, enabling better understanding and interventions for mental health and behavior.

What does a data scientist psychology do?

A data scientist trained in psychology uses data to research trends and patterns of human behavior. Your analysis in this career field can focus on different groups depending on the nature and goals of your research. You can focus on consumer behavior, employee development and retainment, student performance, or behaviors within a community. After you evaluate the data and define trends and common behaviors, your duties include reporting your findings to your employer and suggesting ways to take advantage of psychological trends and patterns to achieve their goals or improve operational performance.

How do data scientists in psychology typically collaborate with researchers and clinicians to apply data-driven insights?

Data Scientists working in psychology often collaborate closely with researchers and clinicians to design studies, analyze behavioral or survey data, and interpret findings in a way that informs treatment, intervention, or theoretical development. This collaboration involves regular meetings to discuss objectives, share data, and validate results. Communication skills are essential, as you’ll need to translate complex statistical concepts into actionable insights for non-technical team members. Additionally, you may work together to publish findings or develop new tools that improve research and clinical outcomes.

What are the key skills and qualifications needed to thrive as a data scientist in psychology, and why are they important?

To thrive as a Data Scientist in Psychology, you need a strong background in statistics, data analytics, and psychological research methods, often supported by degrees in psychology, data science, or a related field. Proficiency with programming languages (such as Python or R), machine learning frameworks, and data visualization tools is typically required. Strong communication, critical thinking, and collaboration skills help translate complex data findings into actionable psychological insights. These skills are crucial for accurately analyzing behavioral data, informing evidence-based interventions, and advancing psychological research.

What is the difference between Data Scientist Psychology vs Data Analyst Psychology?

AspectData Scientist PsychologyData Analyst Psychology
Required CredentialsBachelor's or Master's in Psychology, Data Science, or related fields; programming skillsBachelor's in Psychology, Data Analysis, or related fields; basic statistical knowledge
Work EnvironmentResearch labs, tech companies, healthcare, academiaHealthcare, market research, academic settings, corporate analysis
Employer & Industry UsageTech firms, healthcare providers, research institutionsHealthcare organizations, marketing firms, government agencies

Data Scientist Psychology and Data Analyst Psychology share foundational skills in psychology and data analysis. However, data scientists focus more on advanced modeling, machine learning, and programming, while data analysts primarily handle data cleaning, basic statistical analysis, and reporting. Both roles are vital in understanding psychological data but differ in complexity and technical depth.

What cities are hiring for Data Scientist Psychology jobs?

Cities with the most Data Scientist Psychology job openings:

What are the most commonly searched types of Data Scientist Psychology jobs?

The most popular types of Data Scientist Psychology jobs are:

What states have the most Data Scientist Psychology jobs?

States with the most job openings for Data Scientist Psychology jobs include:

Infographic showing various Data Scientist Psychology job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Lead Data Scientist - Experimentation

State Farm

Bloomington, IL • On-site

Full-time

Medical, Dental, Vision, Retirement

Re-posted 22 days ago


State Farm rating

7.3

Company rating: 7.3 out of 10

Based on 1,562 frontline employees who took The Breakroom Quiz

242nd of 315 rated insurance


Job description

Overview

Being good neighbors – helping people, investing in our communities, and making the world a better place – is who we are at State Farm. It is at the core of how we operate and the reason for our success. Come join a #1 team and do some good!

HYBRID: Qualified candidates must live or relocate within a 180-mile radius of a hub location listed below and should plan to spend time working from home and some time working in the office as part of our hybrid work environment.
HUB LOCATIONS: Bloomington, IL; Dunwoody, GA; Richardson, TX; or Tempe, AZ 

SPONSORSHIP:  Applicants for this position are required to be eligible to lawfully work in the U.S. immediately; employer will not sponsor applicants for U.S. work authorization (e.g. H-1B visa) for this opportunity.

The Selection Process:

1. After submitting your application, our recruitment team will carefully review your qualifications. If your profile aligns with our requirements, you will receive an invite to complete a video recording.

2. If selected to move forward, you will have the opportunity to participate in a live video interview with members of our hiring team. This interview focus on roleplaying interactions with a data science business partner and interpreting code and graphical outputs.

3. The next step is another live video interview with members of our hiring team. This interview will provide a chance for us to further assess your technical expertise and suitability for the role.

4. Following the successful completion of the Hiring Team round, competitive candidates may be invited to the final stage of the process: an in-person final loop interview. This round will involve interviews with members of our hiring panel, allowing us to gain deeper insights into your skills and experiences.


Responsibilities

A Day in the Life of a Data Scientist at State Farm:

As a data scientist on the Enterprise Experimentation Team, you will help business partners examine new ideas by formulating hypotheses and designing experiments to test those hypotheses, allowing them to accurately and confidently quantify the impact of their strategic decisions. You will serve as a subject matter expert, consultant, and advocate for experimentation. Through this role, you will work to educate others on experimentation and grow the knowledge base of experimentation across the company.

Why Join Our Team:

Being on the Enterprise Experimentation Team will help promote your professional growth across multiple areas. First, you will enhance your business acumen by collaborating with a variety of business areas across the Enterprise to produce designed experiments and actionable results. Second, you will enrich your technical skills by facing challenges that require you to dig into your analytic toolbox to identify the right solution. Finally, you will strengthen your communication skills through interactions with business partners that require you to articulate statistical concepts in non-technical ways.

Data Science at State Farm:

In this role, you will share your knowledge and work to increase the use of Experimentation for decision making across the Enterprise. Below are some of the tasks you can expect in the typical day of a data scientist:

  • Develop and validate advanced analytic models, designed experiments, and other data-driven solutions
  • Provide input into and/or build datasets to support solution development
  • Collaborate with other team members on scoping solutions and project decision points
  • Present on technical topics to peers, leadership, and other stakeholders, including non-technical business partners
  • Lead/mentor other data scientists, interns, and other technical work teams
  • Make strategic recommendations on data collection, integration, and retention requirements, incorporating business requirements and knowledge of best practices
  • Serve as a peer reviewer to other model development teams
  • Establish and leverage a network of associates with business domain and data expertise
  • Instill a business-oriented mindset that delivers business outcomes for State Farm’s AI/ML portfolio

Qualifications

Requirements

  • Completed Masters, other advanced degrees, in an analytical field such as statistics, quantitative marketing, experimental psychology, operations research, management science, industrial engineering, etc., with 3+ years of predictive model building experience
  • Practical work experience with, and understanding of, topics associated with A/B testing and other experimental design concepts for business contexts
  • Ability to communicate basic statistical concepts (e.g., statistical significance, confidence intervals, regression models) to business partners
  • Experience building advanced analytic solutions using generalized linear models and at least one of the following: time series analysis, cluster analysis, tree-based algorithms, or neural networks
  • Experience with at least one statistical programming language: Python, R, or SAS

Other Things We Look For:

  • Experience with mixed linear & non-linear model methodologies
  • Experience with statistics-based experimental designs, causal inference, or difference-in-difference based estimation
  • Experience with cloud-based environments (e.g., AWS) or Linux
  • Strong communication skills and the ability to manage multiple, diverse stakeholders across business areas and leadership levels
  • Experience gathering and interpreting business requirements for designing scalable data science solutions in a regulatory environment (e.g., insurance, healthcare, and finance).

Our Benefits

Because work-life balance is a priority at State Farm, compensation is based on our standard 38:45-hour work week!

  • Potential starting salary range: $110,000 - $160,000. Starting salary will be based on skills, background, and experience (High end of the range limited to applicants with significant relevant experience)
  • Potential yearly incentive pay up to 15% of base salary

At State Farm, we offer more than just a paycheck. Check out our suite of benefits designed to give you the flexibility you need to take care of you and your family!

  • Get Paid! On top of our competitive pay, you are eligible for an annual raise and bonus.
  • Stay Well! Focus on you and your family’s health with our robust health and wellbeing programs. State Farm pays most of your healthcare premium, and we offer multiple healthcare plan options, including a high deductible plan. All medical plans provide 100% coverage for in-network preventative care, AND you and your family have access to vision, dental, telemedicine, 24/7 mental health professionals, and much more!
  • Develop and Grow! Take advantage of educational benefits like industry leading training programs, top-notch tuition assistance programs, employee resource groups, and mentoring.
  • Plan Ahead! Plan for those big moments in life with benefits like fertility/IVF/adoption assistance, college coaching, national discount programs, interactive monthly financial workshops, free financial coaching, and more. You can also start a savings account or consider financing through our State Farm Federal Credit Union!
  • Take a Little “You” Time! You will have access to our generous time off policies designed so you can plan around holidays, family events, volunteering, or just to take a relaxing day off. With the opportunity to initially earn up to 20 days annually plus parental leave, paid holidays, celebration day, life leave (40 hours/year), bereavement leave, and community service/education support days, there will be plenty of time for you!
  • Give Back! We offer several ways to give back through our Matching Gift Program, Good Neighbor Grant Program, and the Employee Assistance Fund.
  • Finish Strong! Plan for retirement using free financial advisors and a 401(k) plan with company contributions of up to 7% of your salary.

Visit our State Farm Careers page for more information on our benefits, locations, and the hiring process of joining the State Farm team!

Qualifications:

Requirements

  • Completed Masters, other advanced degrees, in an analytical field such as statistics, quantitative marketing, experimental psychology, operations research, management science, industrial engineering, etc., with 3+ years of predictive model building experience
  • Practical work experience with, and understanding of, topics associated with A/B testing and other experimental design concepts for business contexts
  • Ability to communicate basic statistical concepts (e.g., statistical significance, confidence intervals, regression models) to business partners
  • Experience building advanced analytic solutions using generalized linear models and at least one of the following: time series analysis, cluster analysis, tree-based algorithms, or neural networks
  • Experience with at least one statistical programming language: Python, R, or SAS

Other Things We Look For:

  • Experience with mixed linear & non-linear model methodologies
  • Experience with statistics-based experimental designs, causal inference, or difference-in-difference based estimation
  • Experience with cloud-based environments (e.g., AWS) or Linux
  • Strong communication skills and the ability to manage multiple, diverse stakeholders across business areas and leadership levels
  • Experience gathering and interpreting business requirements for designing scalable data science solutions in a regulatory environment (e.g., insurance, healthcare, and finance).
Education:UNAVAILABLEEmployment Type: FULL_TIME

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