1

Data Science Jobs in Rochester, MI (NOW HIRING)

The Senior Data Scientist plays a critical leadership role in transforming raw data into actionable ... URBAN SCIENCE DOES NOT AND WILL NOT PROVIDE IMMIGRATION RELATED SPONSORSHIP FOR THIS ROLE, NOW OR ...

Agentic AI, AI & Data Science Engineer

Detroit, MI · On-site

$113K - $136K/yr

Work you'll do As an AI and Data Science Engineer III on the AI & Data team, you will be responsible for driving technology-focused client delivery across complex engagements. Working within an ...

next page

Showing results 1-20

Data Science information

See Rochester, MI salary details

$34.5K

$113K

$180.9K

How much do data science jobs pay per year?

As of Jul 12, 2026, the average yearly pay for data science in Rochester, MI is $112,975.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,700.00 and $125,200.00 per year, depending on experience, location, and employer.

Is data science a good career?

Data science is a growing field with high demand for professionals skilled in statistics, programming, and data analysis tools like Python and R. It offers competitive salaries, diverse industry applications, and opportunities for advancement, making it a strong career choice for those with relevant skills and education.

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

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

Is 40 too late for data science?

Data science is a field open to individuals of all ages, and many professionals transition into it later in their careers. Success often depends on acquiring relevant skills such as programming, statistics, and machine learning, which can be learned through online courses, bootcamps, or degrees regardless of age.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What jobs can a Data Scientist do?

A Data Scientist can work in roles such as data analyst, machine learning engineer, data engineer, or business intelligence analyst. These roles involve analyzing large datasets, developing predictive models, and using tools like Python, R, and SQL to support decision-making across various industries.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

What work do you do as a Data Scientist?

A Data Scientist analyzes large datasets to extract insights, build predictive models, and inform business decisions. They use programming languages like Python or R, and tools such as SQL and machine learning frameworks, often working in collaborative environments with data engineers and analysts.

What Does a Data Scientist Do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.
What are the most commonly searched types of Data Science jobs in Rochester, MI? The most popular types of Data Science jobs in Rochester, MI are:
What are popular job titles related to Data Science jobs in Rochester, MI? For Data Science jobs in Rochester, MI, the most frequently searched job titles are:
What job categories do people searching Data Science jobs in Rochester, MI look for? The top searched job categories for Data Science jobs in Rochester, MI are:
What cities near Rochester, MI are hiring for Data Science jobs? Cities near Rochester, MI with the most Data Science job openings:
Infographic showing various Data Science job openings in Rochester, MI as of July 2026, with employment types broken down into 1% As Needed, 81% Full Time, 16% Part Time, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $112,975 per year, or $54.3 per hour.
Senior Data Scientist

Full-time

Posted 9 days ago


Job description

Overview and Summary

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.

Essential Duties and Responsibilities

  • 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.

Qualifications - Education and Experience

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. Reasonabl