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Junior Data & Analytics Jobs in Michigan (NOW HIRING)

Deloitte

Lead AI and Data Science Engineer II

Detroit, MI · On-site

$101K - $133K/yr

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 ...

Deloitte

Lead AI and Data Science Engineer II

Midland, MI · On-site

$88K - $115K/yr

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 ...

Deloitte

Lead AI and Data Science Engineer II

Grand Rapids, MI · On-site

$98K - $129K/yr

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 ...

Ford Motor Company

Data Anchor

Dearborn, MI · On-site

... analytics, automation, and intelligence to the factory floor. You will help build the data ... Proven ability to act as a "Data Anchor," guiding technical architecture and mentoring junior data ...

Ford Motor Company

Data Anchor

Dearborn, MI · On-site

$85K - $192K/yr

... analytics, automation, and intelligence to the factory floor. You will help build the data ... Proven ability to act as a "Data Anchor," guiding technical architecture and mentoring junior data ...

Ford Motor Company

Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Ability to mentor and advise junior team members * Develop exceptional analytical data products using both streaming and batch ingestion patterns on Google Cloud Platform with solid data warehouse ...

Hella

Junior Controller

Northville, MI · On-site

Position Overview As a Junior Controller, you willsupport financial controlling activities for U.S ... analyze financial data Develop and maintain Excel-based reports and dashboards Work with Data ...

Hella

Junior Controller

Northville, MI · On-site

Position Overview As a Junior Controller, you willsupport financial controlling activities for U.S ... analyze financial data Develop and maintain Excel-based reports and dashboards Work with Data ...

Ford Motor Company

Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Ability to mentor and advise junior team members * Develop exceptional analytical data products using both streaming and batch ingestion patterns on Google Cloud Platform with solid data warehouse ...

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All JobsData & Analytics JobsJunior Data & Analytics JobsJunior Data & Analytics Jobs in Michigan

Junior Data Analytics information

See Michigan salary details

$30.1K

$69.2K

$111.1K

How much do junior data & analytics jobs pay per year?

As of Aug 19, 2026, the average yearly pay for junior data & analytics in Michigan is $69,163.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,700.00 and $71,000.00 per year, depending on experience, location, and employer.

What does a junior data & analytics professional do?

A Junior Data & Analytics professional assists in collecting, processing, and analyzing data to help organizations make informed decisions. Their responsibilities often include data cleaning, creating basic reports, and supporting senior analysts with data-driven projects. They typically work with tools like Excel, SQL, and data visualization software to interpret and present findings. This entry-level role is an excellent starting point for building a career in data analysis or business intelligence.

What are some common challenges faced by junior data & analytics professionals in their first year, and how can they overcome them?

Junior Data & Analytics professionals often encounter challenges such as adapting to new data tools, understanding complex datasets, and translating business requirements into analytical solutions. It's common to feel overwhelmed by the volume of data and the pace of ongoing projects. To overcome these challenges, it's helpful to actively seek mentorship from more experienced team members, participate in training sessions, and break down large tasks into manageable steps. Collaborating with colleagues from different departments also offers valuable insights and helps build a broader understanding of the business context.

What are the key skills and qualifications needed to thrive as a junior data & analytics professional, and why are they important?

To thrive as a Junior Data & Analytics professional, you need a solid understanding of statistics, data analysis, and foundational programming skills, typically supported by a relevant degree or coursework. Familiarity with tools such as Excel, SQL, and data visualization platforms like Tableau or Power BI, as well as knowledge of Python or R, is often expected. Strong problem-solving abilities, attention to detail, and effective communication skills help you translate data insights into actionable recommendations. These competencies are crucial for accurately interpreting data, supporting business decisions, and contributing value early in your analytics career.

What is the difference between Junior Data & Analytics vs Data Analyst?

AspectJunior Data & AnalyticsData Analyst
Required CredentialsTypically a bachelor's degree in data-related fields; some certificationsSame as Junior Data & Analytics, often with additional certifications
Work EnvironmentEntry-level, team-based projects, supervised tasksMore independent, project-focused, with increased responsibility
Employer & Industry UsageCommon in tech, finance, marketing firms for entry rolesWidely used across industries for data interpretation roles
Search & Comparison IntentOften searched by beginners or those exploring data careersCompared for career progression or skill level

In summary, Junior Data & Analytics roles are entry-level positions focusing on foundational data tasks, while Data Analysts typically have more experience and handle more complex analysis independently. Both roles share similar credentials and work environments but differ in responsibility and expertise level.

What are the most commonly searched types of Data & Analytics jobs in Michigan?

The most popular types of Data & Analytics jobs in Michigan are:

What are popular job titles related to Junior Data & Analytics jobs in Michigan?

For Junior Data & Analytics jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Junior Data & Analytics jobs in Michigan look for?

The top searched job categories for Junior Data & Analytics jobs in Michigan are:

What cities in Michigan are hiring for Junior Data & Analytics jobs?

Cities in Michigan with the most Junior Data & Analytics job openings:

Junior Data Analytics jobs near you

Lead AI and Data Science Engineer II

Deloitte

Detroit, MI • On-site

$101K - $133K/yr

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

44th 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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