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Social Science Analyst Jobs in Michigan (NOW HIRING)

Deloitte

Lead AI and Data Science Engineer II

Detroit, MI

$101K - $133K/yr

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 ...

Deloitte

Lead AI and Data Science Engineer II

Midland, MI · On-site

$88K - $115K/yr

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 ...

University of Michigan

ORGSTUDY208 GSI

Ann Arbor, MI · On-site

Finally, student teams will complete industry analyses in various geographies to identify future ... Social science (e.g. sociology, political science, psychology, or economics) or related ...

McLaren

Benefits Analyst

Grand Blanc, MI · On-site

Typically, the incumbent also performs professional and analytical work of moderatedifficulty and ... Bachelor's degree in human resources, business, economics, social sciences or a related area and ...

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All JobsSocial Science Analyst JobsSocial Science Analyst Jobs in Michigan

Social Science Analyst information

See Michigan salary details

$41.4K

$65.3K

$121.2K

How much do social science analyst jobs pay per year?

As of Aug 10, 2026, the average yearly pay for social science analyst in Michigan is $65,285.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,700.00 and $81,900.00 per year, depending on experience, location, and employer.

What are some common challenges social science analysts face when working on interdisciplinary research teams?

Social Science Analysts frequently collaborate with professionals from diverse backgrounds such as economists, statisticians, and policy experts. One common challenge is bridging communication gaps and aligning methodologies, since team members may have different approaches to data analysis and interpretation. Successfully navigating these differences requires strong interpersonal skills and adaptability. Analysts who proactively facilitate open dialogue and foster mutual understanding often find the most success in achieving project goals.

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

To thrive as a Social Science Analyst, you need strong analytical skills, a background in social science research, and typically a relevant degree such as sociology, economics, or political science. Proficiency in statistical software (like SPSS, Stata, or R), data analysis tools, and sometimes certifications in research methods are commonly required. Excellent written and verbal communication, critical thinking, and collaboration skills help analysts present findings and work effectively with diverse teams. These abilities are essential to accurately interpret complex data and provide insights that inform policy and program decisions.

What is the difference between Social Science Analyst vs Market Research Analyst?

AspectSocial Science AnalystMarket Research Analyst
Required CredentialsBachelor's degree in social sciences, research methodsBachelor's degree in marketing, business, or social sciences
Work EnvironmentGovernment agencies, research institutions, think tanksPrivate companies, marketing firms, consulting agencies
Employer & Industry UsagePolicy analysis, social programs, academic researchConsumer insights, product development, advertising
Common Search & ComparisonYesYes

Social Science Analysts focus on studying societal issues, policies, and behaviors, often working in government or research settings. Market Research Analysts analyze consumer data and market trends to help companies make business decisions. While both roles involve research and data analysis, their industries, goals, and work environments differ significantly.

What does a social science analyst do?

A Social Science Analyst researches, analyzes, and interprets data related to human behavior, society, and social trends. They often work for government agencies, research organizations, or private companies to help inform policy decisions or solve social problems. Their work involves designing studies, collecting and analyzing statistical data, and preparing reports or presentations that communicate their findings to stakeholders. These professionals typically specialize in areas such as economics, sociology, psychology, or public health.

What does a social science analyst do?

A social science analyst is involved with research into major social issues and typically works for government agencies, universities, and nonprofit organizations. As a social science analyst, your main job duties include analyzing data, conducting interviews and surveys, studying physical evidence, and writing reports. Your goal is to develop new findings about the relationship between society, the human condition, and important social issues to help create better solutions to these problems. This career requires an extensive background in social studies, including at least a bachelor’s degree in history, law, sociology, or a related field. Additional qualifications include relevant work experience, as well as strong research and analytical skills.

More about Social Science Analyst jobs
What are the most commonly searched types of Social Science Analyst jobs in Michigan? The most popular types of Social Science Analyst jobs in Michigan are:
What are popular job titles related to Social Science Analyst jobs in Michigan? For Social Science Analyst jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Social Science Analyst jobs in Michigan look for? The top searched job categories for Social Science Analyst jobs in Michigan are:
What cities in Michigan are hiring for Social Science Analyst jobs? Cities in Michigan with the most Social Science Analyst job openings:
What are popular job titles related to Social Science Analyst jobs in MI? For Social Science Analyst jobs in MI, the most frequently searched job titles are:
Social Science Analyst jobs near you
Infographic showing various Social Science Analyst job openings in Michigan as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 20% Part Time, 1% Temporary, and 3% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $65,285 per year, or $31.4 per hour.

Lead AI and Data Science Engineer II

Deloitte

Detroit, MI

$101K - $133K/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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