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Data Science Associate Jobs in Michigan (NOW HIRING)

Headquartered in Amelia, Ohio, and with associates located across the United States, we are part of ... Join our dynamic, centralized Data Science team as we execute our AI/ML roadmap! We focus on ...

... Associate & Summary The Opportunity As a CTIO - AI Engineer - Experienced Associate, you will ... Accounting, Analytics/Data Science, Artificial Intelligence/Robotics, Business Administration ...

Mentor and train associate data scientists About you * 3 years of experience working with large data sets in one or more of the following environments - Hadoop, AWS, Azure or GCP * 3 years of ...

Mentor and train associate data scientists About you * 3 years of experience working with large data sets in one or more of the following environments - Hadoop, AWS, Azure or GCP * 3 years of ...

Data Science and/or Data Analytics * Biostatistics * Information Management * Bioinformatics * Mathematics * Epidemiology Work Experience/Skills: Minimum: * Up to three years' experience in a ...

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

Associate Data Engineer - Voice of the Customer Analytics Position Overview The Associate Data ... Required Qualifications * Bachelor's degree in engineering, analytics, computer science ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... As a Senior Associate you will analyze complex problems, mentor others, and maintain elevated ...

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Data Science Associate information

See Michigan salary details

$50.1K

$59.3K

$112.4K

How much do data science associate jobs pay per year?

As of Jul 8, 2026, the average yearly pay for data science associate in Michigan is $59,302.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,400.00 and $51,900.00 per year, depending on experience, location, and employer.

How does a Data Science Associate typically collaborate with other departments or teams within an organization?

Data Science Associates frequently work cross-functionally, partnering with teams such as engineering, product management, and business analytics to understand project requirements, share findings, and implement data-driven solutions. Collaboration often involves translating complex data results into actionable insights for non-technical stakeholders, ensuring alignment on project goals and deliverables. This role requires strong communication skills, as associates routinely participate in meetings, present analyses, and gather feedback to refine their models or analyses. Effective teamwork helps ensure that data science initiatives support broader business objectives.

Is 40 too late for data science?

Age is not a barrier to becoming a data science associate; many professionals transition into data science later in their careers. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications, regardless of age.

Is an Associates in data science worth it?

An associate's degree in data science can provide foundational skills in data analysis, programming, and statistics, which may help entry-level candidates qualify for junior data science roles. However, many employers prefer candidates with a bachelor's degree or higher, and practical experience or certifications in tools like Python, R, or SQL can enhance job prospects. The value depends on career goals and the specific requirements of potential employers.

What can I do with an associate's degree in data science?

A Data Science Associate with an associate's degree can work as a data analyst, supporting data collection, cleaning, and basic analysis using tools like Excel, SQL, and Python. They often assist in generating reports, visualizations, and insights under supervision, and may pursue certifications to enhance their skills for more advanced roles.

What are Data Science Associates?

Data Science Associates are early-career professionals who support data-driven projects by collecting, cleaning, analyzing, and interpreting large datasets. They typically work under the guidance of more experienced data scientists and help build predictive models, generate reports, and provide insights to inform business decisions. This role often requires proficiency in programming languages like Python or R, familiarity with statistical methods, and strong problem-solving skills. Data Science Associates play a crucial part in transforming raw data into actionable information for organizations.

What is the role of an associate data scientist?

An associate data scientist supports data analysis and modeling tasks by cleaning and processing data, developing algorithms, and creating visualizations. They often work under supervision to assist in building predictive models and may use tools like Python, R, or SQL to analyze data and generate insights.

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

To thrive as a Data Science Associate, you need strong analytical skills, a solid foundation in statistics and mathematics, and proficiency in programming languages like Python or R, often supported by a degree in data science, computer science, or a related field. Familiarity with machine learning frameworks, data visualization tools, and database systems such as SQL is typically required. Excellent problem-solving abilities, effective communication, and collaboration skills help you translate complex data insights into actionable business strategies. These skills are vital for extracting meaningful value from data and supporting data-driven decision-making within organizations.

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

AspectData Science AssociateData Analyst
Required CredentialsBachelor's degree in Data Science, Statistics, or related field; some roles prefer certifications in data analysis or programmingBachelor's degree in Statistics, Mathematics, or related field; often no advanced certifications required
Work EnvironmentCollaborates with data scientists and engineers; involved in building models and algorithmsFocuses on data collection, cleaning, and reporting; supports decision-making
Employer & Industry UsageUsed in tech, finance, healthcare, and consulting firms for data-driven projectsCommon across various industries for business insights and reporting

The Data Science Associate role typically involves more technical work like building models and applying machine learning, whereas Data Analysts focus on interpreting data and creating reports. Both roles require strong analytical skills, but Data Science Associates often have a deeper understanding of programming and statistical modeling.

What are the most commonly searched types of Data Science jobs in Michigan? The most popular types of Data Science jobs in Michigan are:
What are popular job titles related to Data Science Associate jobs in Michigan? For Data Science Associate jobs in Michigan, the most frequently searched job titles are:
What cities in Michigan are hiring for Data Science Associate jobs? Cities in Michigan with the most Data Science Associate job openings:
Infographic showing various Data Science Associate job openings in Michigan as of July 2026, with employment types broken down into 1% As Needed, 69% Full Time, 27% Part Time, 1% Temporary, and 2% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $59,302 per year, or $28.5 per hour.

Full-time

Posted 18 days ago


Job description

We are Automotive Business Scientists. We empower our clients to turn overwhelming industry data into discovery, action and measured success.  We are unique market leaders because we find and examine possibilities through the clarity of a scientific lens. To solve the toughest client challenges, we need curious, creative and dedicated people to join our team. 

We search out individuals who align with our core values and who adhere to the highest standards of integrity and ethics in everything they do.  Our company is filled with the brightest minds and the biggest hearts at every level. We recognize that personal success takes on many different forms of the course of our lives – both professional and personally – so we provide a myriad of benefits and programs focused on Wellbeing, Growth, Community and Recognition.  One size does not fit all, so we encourage every Urban Scientist to discover their own formula for success.  If this sounds like the kind of company you would like to work with, Apply Now!

POSITION OVERVIEW: The Senior Data Scientist plays a critical leadership role in transforming raw data into actionable insights that drive strategic decisions. This role requires the integration of advanced analytics, machine learning, and statistical modeling to support product development, client solutions, and internal operations. The Advanced Analytics Senior Data Scientist has responsibility to build and maintain advanced analytical AI, machine learning and forecasting pipelines. Essential duties also include data extraction, preparation and visualization. Additionally, the Senior Data Scientist is responsible for the production of scheduled and ad-hoc quality reports and validation of model performance and accuracy. The Advanced Analytics Senior Data Scientist is the lead liaison with clients that use or integrate the output of AI, machine learning and forecasted data pipelines or studies.

This role has current Hybrid Workplace flexibility local to our Detroit, MI office location. Candidate must be available and willing to work in-person approximately twice per week (currently Tuesdays and Wednesdays).

URBAN SCIENCE DOES NOT AND WILL NOT PROVIDE IMMIGRATION RELATED SPONSORSHIP FOR THIS ROLE, NOW OR IN THE FUTURE.


  • Support the development of embedded advanced analytics into Urban Science solutions using Azure AI/ML, SQL, Python and/or SAS.
  • Responsible for building and maintaining advanced analytical models, including supervised machine learning models, predictive models, and time-series models.
  • Tracks, processes, analyzes and verifies data in order to improve accuracy and quality.
  • Creates presentation materials that showcase research findings and results; Presents results to internal clients.
  • Works with the Learning team to analyze, develop, and maintain appropriate training and certification materials for internal employees.
  • Develops complex machine learning models and updates existing models to validate effectiveness for various clients using techniques such as regression, decision trees, random forests, artificial neural nets, survival analysis, and/or time series.
  • Collects, imports, and organizes relevant data within AI & machine learning software such as Azure, Fabric, SAS and/or Python to support modeling development and maintenance.
  • Collaborates with internal clients to collect requirements and specifications in order to build complex machine learning analyses that are embedded into corporate software and processes.
  • Uses SQL server to extract, process and prepare data for machine learning modeling.
  • Attends project meetings and participates in presenting project status updates, conclusions and results.
  • Adheres to quality control standards for Urban Science and client organizations. Designs, develops, and maintains quality assurance (QA) reports of machine learning processes using tools such as SAS, MS Excel, Tableau, and/or MS Power BI.
  • Coordinates with individuals or teams to complete analyses, tasks and projects on time and with high quality. Responsible for creating estimates and proposals for projects and budgeting purposes.
  • Effectively responds to client inquiries/requests in a timely manner to help improve client satisfaction.
  • Proactively communicates with management to provide updates and report issues in a timely manner.
  • Actively supports and participates in training programs to achieve targeted development objectives. May have responsibility to train / mentor other Associates in processes, procedures and methodologies.
  • Works with manager in completing own annual goal setting and performance review in a timely manner.
  • Plans, organizes, develops and delivers client requested reports and deliverables on time, adhering to client requested specifications.
  • Works with manager to prioritize other duties as assigned. Maintain personal task list using tools such as AzureDevOps for project and task management.
  • Partners with the Practice organization to invent new advanced analytical methodologies and manages the integration of new methodologies into Practice solutions.
  • Provides guidance and oversight for advanced analytics projects and analyses that occur on account teams teams globally, including defining scope, cost estimates, schedules, and selection of appropriate analytical methods.
  • Consults with local account teams and engages with external clients, to provide appropriate analytical methodologies that will meet client needs and requirements, including reviewing SOWs and providing sales materials.
  • Researches, evaluates and develops new potential AI/ML/forecasting/statistical methodologies, processes and procedures for application.

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

  • Verbal Communication: Requires the ability to compose and verbally deliver information of varying levels, using appropriate grammar, tone, inflection and non-verbal cues, while also listening to and correctly deciphering verbal communication delivered by others.
  • Written Communication: Requires the ability and capacity to communicate ideas, facts and data in writing using appropriate grammar, syntax and sentence structure.
  • Analytical Thinking: Requires the ability to understand a situation by breaking it apart into smaller pieces, and/or tracing the implications of a situation in a step-by-step causal way.
  • Conceptual Thinking: Requires the ability to understand a situation or problem by putting the different pieces together to see the bigger picture.
  • Information Seeking: Requires the drive to gain a deeper understanding of work related issues or events by making a concerted effort to gather information and seek out development opportunities.
  • Flexibility/Adaptability: Requires the ability to adapt to and work effectively within a variety of situations, individuals or groups, as well as understand and appreciate different and opposing perspectives.
  • Results Oriented: Requires the ability to strive for optimal results by taking responsibility for timeliness, commitment to task and adherence to performance standards.
  • Initiative: Requires the drive to go above and beyond in order to improve or enhance job results.
  • Self-Confidence: Requires the ability to express confidence in dealing with challenging circumstances, in reaching decisions or forming opinions and in handling failures or set-backs constructively.
  • Organizational Commitment: Requires the ability and willingness to align his/her own behavior with the needs, priorities and goals of the organization.
  • Ethics & Integrity: Requires the ability to behave in a trustworthy & transparent manner.
  • Teamwork & Cooperation: Requires the ability to work cooperatively with others and be part of a team.
  • Team Leadership: Requires the ability to effectively take a role as leader of a team with a desire to help the group achieve business related outcomes.
  • Self-Control: Requires the ability to keep emotions under control and to restrain from negative actions or behaviors.
  • Quality Control: Requires the ability to monitor and check one’s own work and the work of others, having responsibility over deliverables ensuring high quality and accuracy
  • Customer Service Oriented: Requires the ability to follow up on a client inquiry, request or complaint by taking routine or required action and will keep the client up to date on progress of tasks/projects/requests.
  • Interpersonal Understanding: Requires the ability to understand other’s feelings and concerns, and to value individual differences in people.
  • Relationship Building: Requires the ability to effectively build and maintain friendly, warm relationships or networks of contacts with clients/customers.
  • Assertiveness: Requires the ability and intent to appropriately display assertive behaviors to ensure others follow given directions.
  • Developing & Coaching: Requires the ability, desire and intent to teach and foster the development and long term capability of one or more employees by providing coaching, direction and feedback to enhance performance.
  • Strategic Influence: Requires the ability to effectively persuade, convince, and influence others in order to gain support to achieve work related goals/objectives.
  • Organization & Time Management: Requires advanced capability to prioritize competing demands, manage multiple concurrent tasks and effectively manage meeting agendas.
  • Project Management: Requires strong knowledge of project management principles and fundamentals including the ability to estimate work efforts, define work plans, delegate work, monitor progress and report schedule variances and scope changes.
  • Math & Statistics: Requires extensive knowledge of a statistical modeling language (SAS, R, or Python); requires formal education/training in advanced analytical modeling techniques, mathematics, statistics, or econometrics. Requires knowledge of machine learning techniques such as time-series forecasting, clustering, regression, decision trees, GLMs, neural networks, survival analysis.
  • MS Office: Requires advanced knowledge of MS Excel for charting and graphing of data, writing formulas, utilizing functions, and filtering, sorting and formatting of data; intermediate knowledge of MS Word, and PowerPoint is required.
  • Database: Requires advanced knowledge of relational database concepts, including diagnostics and resolution of database errors, gathering and manipulating data manually; knowledge and experience with SQL is required.
  • Technical/Software: Requires advanced proficiency in SAS or Python; Experience building ML pipelines is preferred. Experience with ML Ops packages (e.g. scikit-learn) strongly preferred.
  • Sales & Business Development: Ability to identify potential new opportunities from the client and proactively communicate those opportunities to management is required; knowledge and understanding of sales and business development processes is strongly preferred.
  • Budgeting/Finance: Requires basic knowledge of budgeting philosophy and principles; requires ability to provide labor cost estimates for budgeting purposes.
  • Negotiation: Knowledge and understanding of pricing, scope, cost estimates and internal/external impacts is strongly preferred

EDUCATION AND EXPERIENCE

  • University degree in an appropriate technical or analytical field required (i.e., computer science, engineering, applied mathematics, statistics, econometrics, analytics, etc.) from an accredited college or university, or equivalent foreign institution; Masters degree in a related field preferred
  • Requires 5+ years experience building and implementing advanced analytical techniques (machine learning, artificial intelligence, forecasting, econometrics and/or statistical modeling)
  • Requires experience implementing models in complex industry applications
  • Requires working knowledge of API integration and/or model deployment workflows
  • Strong proficiency with AI, machine learning or statistical modeling using Azure AI/ML, SAS and/or Python required
  • Proficiency with SQL required
  • Requires experience with machine learning frameworks (e.g., scikit-learn, TensorFlow)
  • Proficiency in data visualization tools preferred (Tableau, PowerBI, Fabric, or similar)
  • Experience in developing and deploying time series forecasting models, including ARIMA, Exponential Smoothing, UCM, State Space, and other advanced forecasting methodologies preferred 
  • Experience developing ML Ops pipelines using Azure AI cloud computing & LLMs preferred 
  • Experience with geographic analysis or GIS preferred
  • Experience with Azure DevOps and Agile development concepts preferred


CERTIFICATES, LICENSES, REGISTRATIONS:

  • Network Apprentice certification preferred (for internal applicants)

WORK ENVIRONMENT 

The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.