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Data Science Graduate Jobs in Michigan (NOW HIRING)

Analytical functions such as Structuring & Valuation, Risk Management or Data Science, and more ... While you're on our graduate journey, we're committed to providing you with a range of ...

Data Collection and Analysis: Produce accurate reports for others by collecting data from a variety ... Bachelor's Degree or Equivalent Level in Engineering, Geology, Environmental Science or related ...

Data Quality Assurance Intern

Lansing, MI · On-site

$15.25 - $20.25/hr

... graduate program pursuing one of the following?: Public Health, Public Administration, Data Science, Environmental Health, or a related field * Yes * No 02 Current Academic Institution: 03 What ...

Data Collection and Analysis: Produce accurate reports for others by collecting data from a variety ... Bachelor's Degree or Equivalent Level in Engineering, Geology, Environmental Science or related ...

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Data Science Graduate information

See Michigan salary details

$32.7K

$107K

$171.3K

How much do data science graduate jobs pay per year?

As of Jul 13, 2026, the average yearly pay for data science graduate in Michigan is $106,978.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,900.00 and $118,500.00 per year, depending on experience, location, and employer.

What is the difference between Data Science Graduate vs Data Analyst?

AspectData Science GraduateData Analyst
Required CredentialsDegree in Data Science, Computer Science, or related fieldDegree in Statistics, Mathematics, or related field
Work EnvironmentInternships, entry-level roles in tech or finance companiesBusiness, marketing, or finance departments across industries
Employer & Industry UsageTech firms, startups, research institutionsCorporations, consulting firms, government agencies
Common Search & ComparisonYesYes

Data Science Graduates typically focus on building models, machine learning, and advanced analytics, often requiring programming skills and a strong foundation in data science concepts. Data Analysts primarily interpret data, generate reports, and support decision-making with statistical tools. While both roles analyze data, Data Science Graduates usually work on more complex modeling tasks, whereas Data Analysts focus on data interpretation and visualization.

What types of projects and responsibilities can a Data Science Graduate expect in their first role?

As a Data Science Graduate, you can expect to work on a variety of projects such as data cleaning, exploratory data analysis, and building predictive models under the guidance of senior team members. Typical responsibilities include preparing datasets, validating model outputs, and presenting findings to both technical and non-technical stakeholders. You’ll often collaborate with data engineers, software developers, and business analysts to ensure your solutions align with organizational goals. This early-career role is a great opportunity to learn industry-standard tools, gain mentorship, and build a portfolio of impactful projects.

What are the key skills and qualifications needed to thrive as a Data Science Graduate, and why are they important?

To thrive as a Data Science Graduate, you need strong analytical skills, a solid understanding of statistics, and proficiency in programming languages like Python or R, typically backed by a relevant degree. Familiarity with data visualization tools (e.g., Tableau), machine learning frameworks (e.g., scikit-learn, TensorFlow), and database management systems (e.g., SQL) is highly valuable. Strong communication, problem-solving, and adaptability help you convey insights and collaborate effectively with diverse stakeholders. These skills enable you to extract meaningful information from data, drive informed decisions, and add value to organizations in a data-driven world.

What are Data Science Graduates?

Data Science Graduates are individuals who have recently completed a degree or certification program in data science or a related field. They possess foundational knowledge in statistics, programming, and data analysis, and are equipped to apply these skills in real-world scenarios. These graduates are typically proficient in tools such as Python, R, SQL, and data visualization platforms, and are prepared for entry-level roles in data analytics, machine learning, or business intelligence. Their education often includes hands-on projects and internships to build practical experience. Data Science Graduates are in high demand across industries that rely on data-driven decision making.
What job categories do people searching Data Science Graduate jobs in Michigan look for? The top searched job categories for Data Science Graduate jobs in Michigan are:
What cities in Michigan are hiring for Data Science Graduate jobs? Cities in Michigan with the most Data Science Graduate job openings:

Mathematical Statistician (Data Scientist) - Direct Hire

Criminal Investigation & Law Enforcement | IRS Careers

Portage, MI

$74K/yr

Other

Posted 5 days ago


Job description

WHAT IS DATA AND ANALYTICS?
A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions

  • Position(s) are to be filled in the following area(s):
    • DAO- Data and Analytics Office (DAO)-RESEARCH, APPLIED ANALYTICS & STATISTICS (RAAS)
  • Consider each location carefully when applying. If you are selected for a location, that location will become your official post of duty.
REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILSQualifications:Federal experience is not required. Experience may have been gained in the public sector, private sector or through Volunteer Service. One year of experience refers to full-time work; part-timework is considered on a prorated basis. To ensure full credit for your work experience, please indicate dates of employment by month/day/year, and indicate number of hours worked per week, on your resume.
You must meet the following requirements by the cut-off dates as shown in announcement under the 'How to Apply' section.
IOR BASIC REQUIREMENTS GS-1529 Mathematical Statistician (Data Scientist):
You must have a degree that included courses in mathematics and statistics totaling at least 24 semester hours. This course work must have included a minimum of 12 semester hours of mathematics, and 6 semester hours were in statistics. Courses acceptable toward meeting the mathematics course requirement must have included at least four of the following: differential calculus, integral calculus, advanced calculus, theory of equations, vector analysis, advanced algebra, linear algebra, mathematical logic, differential equations, or any other advanced course in mathematics for which one of these was a prerequisite. Courses in mathematical statistics or probability theory with a prerequisite of elementary calculus or more advanced courses will be accepted toward meeting the mathematics requirements, with the provision that the same course cannot be counted toward both the mathematics and the statistics requirement.
OR
Combination of education and experience -- includes at least 24 semester hours of mathematics and statistics, including at least 12 hours in mathematics and 6 hours in statistics, as described above; and Experience that showed evidence of statistical work such as (a) sampling, (b) collecting, computing, and analyzing statistical data, and (c) applying known statistical techniques to data such as measurement of central tendency, dispersion, skewness, sampling error, simple and multiple correlation, analysis of variance, and tests of significance.
AND
GS-1529-11 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-09 grade level in the Federal service. Examples of specialized experience for this position may include:
  1. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science projects.
  2. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  3. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  4. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  5. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  6. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.
OR
EDUCATION: You may substitute education for specialized experience specialized experience as follows: Three (3) full academic years of progressively higher-level graduate education in Mathematics, statistics, or related fields.
OR
Ph. D. or equivalent doctoral degree Mathematics, statistics, or related field of study from an accredited college or university.
OR
Combination of education and experience: A combination of qualifying graduate education and experience equivalent to the amount required.
GS-1529-12 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-11 grade level in the Federal service. Examples of specialized experience for this position may include:
  1. Experience applying knowledge of statistical theories, principles, concepts and practices that relate to experimental design, data analysis, sampling, forecasting, quality control, and operations research to understand, model and improve program operations.
  2. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science project.
  3. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  4. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  5. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  6. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  7. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.

GS-1529-13 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-12 grade level in the Federal service.
Examples of specialized experience for this position may include:
  1. Experience applying project management principles on a data science project.
  2. Experience planning and executing a variety of data science and/or analytics projects.
  3. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science project.
  4. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  5. Experience working with multiple data types and formats as a part of a data science project.
  6. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  7. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  8. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  9. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.
AND
You must also meet the following requirements:
  • MINIMUM AGE REQUIREMENT: Minimum age for federal employment is 18 years old, or at least 16 years old and have:
    • Graduated from high school or been awarded a certificate equivalent to graduating from high school; or
    • Completed a formal vocational training program; or
    • Received a statement from school authorities agreeing with your preference for employment rather than continuing your education

For more information on qualifications please refer to OPM's Qualifications Standards.Education:A college or university degree generally must be from an accredited (or pre-accredited) college or university recognized by the U.S. Department of Education. For a list of schools which meet these criteria, please refer to Department of Education Accreditation page.
FOREIGN EDUCATION: Education completed in foreign colleges or universities may be used to meet the requirements. You must show proof the education credentials have been deemed to be at least equivalent to that gained in conventional U.S. education program. It is your responsibility to provide such evidence when applying. Click here (Section 3, Explanation of Terms) or here for Foreign Education Credentialing instructions.
We recommend choosing an evaluator from a member organization of one of the following national associations of credential evaluation services: National Association of Credential Evaluation Services (NACES) or Association of International Credentials Evaluators (AICE).Employment Type: OTHER