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Director Of Data Science Jobs in Michigan (NOW HIRING)

Grow the technical capabilities of the scientist community within the CCA Applied Analytics ... Work cross-functionally across data engineering, delivery teams, software delivery, other business ...

D degree with emphasis on coursework of a quantitative nature (e.g., Statistics, Computer Science ... assign, direct and control the work of employees under their supervision. PRIVACY NOTICE TO ...

Data Scientist

Plymouth, MI · On-site

$90 - $130/hr

Minimum of 3 years of experience in data analysis, data science, systems analysis, business intelligence, financial analytics, or a related role; experience applying ML/AI concepts in a business ...

Our data science engineers employ statistical modelling and measurement frameworks to model the distribution of road events in the real world, and inform our long-term validation and ML training data ...

Master's degree in quantitative fields, such as Data Science, Engineering, Operations Research, Industrial Engineering, Statistics, Mathematics OR Computer Science or equivalent combination of ...

This role is ideal for someone with 2+ years of direct Foundry development experience and no more than 5 years of total professional experience in analytics, data science, or data engineering. The ...

This role is ideal for someone with 2+ years of direct Foundry development experience and no more than 5 years of total professional experience in analytics, data science, or data engineering. The ...

Showing results 41-60

Director Of Data Science information

See Michigan salary details

$47.1K

$135K

$212.7K

How much do director of data science jobs pay per year?

As of Aug 23, 2026, the average yearly pay for director of data science in Michigan is $134,987.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,900.00 and $165,200.00 per year, depending on experience, location, and employer.

What are some common challenges faced by a director of data science when leading cross-functional teams?

As a Director of Data Science, one of the key challenges is aligning the goals of data science teams with those of product, engineering, and business stakeholders. This often involves translating complex technical findings into actionable insights that non-technical colleagues can understand and use. Additionally, managing resource allocation and prioritizing projects across multiple departments can be demanding, especially in fast-paced environments. Building a collaborative culture and fostering open communication are crucial for overcoming these challenges and ensuring data-driven strategies deliver business value.

What are the key skills and qualifications needed to thrive as a director of data science, and why are they important?

A Director of Data Science needs advanced expertise in statistical analysis, machine learning, and data strategy, typically supported by a graduate degree in a quantitative field and significant industry experience. Familiarity with big data platforms (e.g., Hadoop, Spark), programming languages (Python, R), and cloud-based analytics tools, as well as experience managing data science teams, is essential. Strong leadership, communication, and business acumen are key soft skills for aligning technical work with organizational goals and influencing stakeholders. These skills are crucial for driving data-driven decision-making and maximizing the strategic impact of data science initiatives within the organization.

What is the difference between Director Of Data Science vs Data Scientist?

AspectDirector Of Data ScienceData Scientist
Required CredentialsAdvanced degrees (Master's or PhD), leadership experienceBachelor's or Master's in Data Science, Computer Science, or related fields
Work EnvironmentStrategic planning, team management, cross-department collaborationData analysis, model development, coding, and experimentation
Employer & Industry UsageTech companies, finance, healthcare, large enterprisesStartups, tech firms, research institutions, various industries

The main difference between a Director Of Data Science and a Data Scientist lies in their scope of responsibilities. The Director oversees strategic initiatives, manages teams, and aligns data projects with business goals, while Data Scientists focus on analyzing data, building models, and deriving insights. Both roles require strong technical skills, but the Director's role emphasizes leadership and strategic planning.

What does a director of data science do?

A director of data science oversees data science teams, develops strategies for data analysis and modeling, and ensures the implementation of data-driven solutions to support business goals. They often manage projects, collaborate with other departments, and have expertise in statistical methods, machine learning, and data management tools. Strong leadership, communication skills, and experience with programming languages like Python or R are essential for this role.

What are the most commonly searched types of Of Data Science jobs in Michigan?

The most popular types of Of Data Science jobs in Michigan are:

What cities in Michigan are hiring for Director Of Data Science jobs?

Cities in Michigan with the most Director Of Data Science job openings:

Infographic showing various Director Of Data Science job openings in Michigan as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 13% Part Time, 2% Temporary, 3% Contract, and 1% Nights. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $134,987 per year, or $64.9 per hour.

Full-time

Posted 9 days ago


Job description

GENERAL SUMMARY: 

The Data Scientist, Healthcare Analytics assists the Senior Data Scientist, Healthcare Analytics and other business analysts with working with business users to fully understand their needs for data science solutions. Works with a variety of data sources, both internal and external, big and small, structured and unstructured formats to build analytic models utilizing machine-learning techniques. Partners with the IT group to ensure that the data is sourced from the right location for data science model building. Participates in the development of project deliverables, especially documentation, for data science deliverables. As a team player, interacts with various other roles such as data engineers, business analysts and others. The Data Scientist, Healthcare Analytics solves analytical problems and develops cutting edge solutions to business problems. Should also be skilled at extracting, transforming, and analyzing data using a variety of common analytical tools and statistical techniques. Should be able to present findings in a compelling manner to both a business and non-technical audience. The position requires a team player that is eager to continue to learn and evolve with business needs and changes in the data and business environment. 

EDUCATION/EXPERIENCE REQUIRED: 

  • Must have an undergraduate (BS) degree in Statistics, Mathematics, Econometrics, Operations Research, Public Health, and Epidemiology or another related field. MS degree is preferred. 
  • Three plus (3+) years of professional work experience. 
  • Two plus (2+) years of experience involving quantitative data analyses for problem solving in US Healthcare industry. 
  • Two plus (2+) years of experience with predictive, forecasting, and optimization problem solving using data analytics tools like Python, R or SAS. 
  • Exposure of working with cloud Big Data Stack to orchestrate data gathering, cleansing, preparation and modelling preferred. 
  • Advanced SQL skills working with RDBMSs such as Oracle, SQL Server, etc. 
  • Experience working with data visualization tools or Data Visualization Designers in Tableau or Power BI. 
  • Also, experience with data visualization for analytic models in Rshiny, GGPlot, Qlik, Alteryx, Flask, D3, etc. used to tell the data story to business users to foster adoption of analytic outputs created preferred. 
  • Exceptionally skilled in machine learning, data analytics, pattern recognition and predictive modelling.
  •  Strong communication and presentation skills. Effective communication and storytelling skills. 
  • Energy and enthusiasm. Passion for learning and contributing to development. A true team player. Collaborative mindset for effective communication across teams.
Additional Information
  • Organization: Corporate Services
  • Department: Helios Enter Data Wrhse IT Exp
  • Shift: Day Job
  • Union Code: Not Applicable