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Executive Data Science Jobs in Michigan (NOW HIRING)

OneMagnify

Data Scientist

Detroit, MI · On-site

... executive-level audiences, with the judgment to handle complex or sensitive inquiries with care ... BA/BS in Computer Science, Statistics, Mathematics, MIS, Marketing Research, or a related ...

Conclusive Marketing

Data Scientist

Detroit, MI · On-site

... executive-level audiences, with the judgment to handle complex or sensitive inquiries with care ... BA/BS in Computer Science, Statistics, Mathematics, MIS, Marketing Research, or a related ...

General Motors

Staff Data Scientist

Warren, MI · On-site

Lead the design, development, and implementation of complex data science solutions to address ... executives in business terms. * Evidence of being able to transfer solutions to business ...

General Motors

Staff Data Scientist

Warren, MI · Hybrid

Lead the design, development, and implementation of complex data science solutions to address ... executives in business terms. * Evidence of being able to transfer solutions to business ...

Partify

Data Scientist

Warren, MI · On-site

What to Expect As a Data Scientist, you will be responsible for helping us in a variety of ... This posting was written by the CEO without the use of any AI.

Venteon

Senior Director Data Analytics & AI

Novi, MI · On-site

This executive-level position will drive the organization's vision across Master Data Management ... Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or a related ...

Hospice of Michigan

Data Scientist

Ann Arbor, MI

... executive leadership; and supporting CMS Hospice Quality Reporting Program (HQRP) submissions and other regulatory requirements. The role serves as a liaison between the analytics function and ...

Hospice of Michigan

Data Scientist

Ann Arbor, MI · On-site

... executive leadership; and supporting CMS Hospice Quality Reporting Program (HQRP) submissions and other regulatory requirements. The role serves as a liaison between the analytics function and ...

Hospice of Michigan

Data Scientist

Ann Arbor, MI · On-site

$100 - $130/hr

... executive leadership; and supporting CMS Hospice Quality Reporting Program (HQRP) submissions and other regulatory requirements. The role serves as a liaison between the analytics function and ...

Vervint

Director of Data Intelligence

Grand Rapids, MI · On-site +1

Build and lead a high-performing team of data scientists, analysts, and engineers. * Promote a ... Strong executive presence and ability to communicate complex concepts to both technical and non ...

Vervint

Director of Data Intelligence

Grand Rapids, MI · On-site

Build and lead a high-performing team of data scientists, analysts, and engineers. * Promote a ... Strong executive presence and ability to communicate complex concepts to both technical and non ...

Tech Mirrors

AI Specialist

Rochester, MI · On-site

$120 - $180/hr

The ideal candidate will possess a strong background in machine learning, data science, AI ... Prepare technical documentation, presentations, and executive updates on AI initiatives and ...

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Executive Data Science information

What is executive data science?

Executive Data Science refers to the leadership and management of data science initiatives within an organization. Professionals in this role are responsible for setting the strategic direction for data-driven projects, overseeing data teams, and ensuring that data science efforts align with business goals. They bridge the gap between technical teams and executives, translating analytical insights into actionable business strategies. Typically, Executive Data Scientists have a blend of technical expertise and strong business acumen, enabling them to make high-level decisions that impact the organization’s growth and innovation.

What skills and qualifications are needed to thrive as an executive data scientist?

To thrive as an Executive Data Scientist, you need deep expertise in statistics, machine learning, and data analysis, typically supported by an advanced degree in a quantitative field. Proficiency with data platforms (such as SQL, Hadoop, or Spark), programming languages (like Python or R), and familiarity with data visualization tools is essential, along with certifications like Certified Analytics Professional (CAP) being advantageous. Strategic vision, leadership, and the ability to communicate complex insights to non-technical stakeholders are vital soft skills. These competencies drive effective data-driven decision-making and ensure alignment between analytics initiatives and business objectives.

How does an executive data scientist typically collaborate with other departments to drive data-driven decision making?

Executive Data Scientists frequently work cross-functionally with departments such as marketing, product, finance, and operations to identify key business challenges and opportunities where data can provide strategic insights. They lead or advise interdisciplinary teams, translate complex analytics into actionable recommendations, and often present findings to senior leadership or stakeholders. Building strong relationships and understanding business objectives are crucial, as these collaborations enable the alignment of data science initiatives with organizational goals.

What is the difference between Executive Data Science vs Data Scientist?

AspectExecutive Data ScienceData Scientist
CredentialsAdvanced degrees (Master's/PhD), leadership experienceBachelor's or Master's in Data Science, Computer Science, or related fields
Work EnvironmentStrategic, leadership-focused, often in executive officesHands-on data analysis, modeling, coding in technical teams
Employer & Industry UsageSenior roles in tech, finance, consulting, and large organizationsTech companies, startups, research institutions, various industries

Executive Data Science roles focus on strategic decision-making, leadership, and overseeing data initiatives, while Data Scientists are primarily involved in technical data analysis and modeling. Both roles require strong analytical skills, but Executive Data Scientists combine technical expertise with leadership responsibilities.

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 Executive Data Science jobs in Michigan?

For Executive Data Science jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Executive Data Science jobs in Michigan look for?

The top searched job categories for Executive Data Science jobs in Michigan are:

What cities in Michigan are hiring for Executive Data Science jobs?

Cities in Michigan with the most Executive Data Science job openings:

Executive Data Science jobs near you

Data Scientist

OneMagnify

Detroit, MI • On-site

Full-time

Re-posted 18 days ago

Job description

Data Scientist
Role Summary
OneMagnify's Data Scientists sit at the intersection of client strategy and technical delivery, turning complex business questions into models, analyses, and insights that clients actually use to make decisions. You'll work alongside Data Engineering, AI, and cross-functional teams to design and deploy solutions that span the full analytics lifecycle, from data integration and quality to predictive modeling and advanced analytics. This role is a fit for someone who wants to do serious technical work and see it matter in the real world.
The Impact You'll Have
The clients you'll support are making high-stakes decisions about customers, markets, and products. Your models, including forecasting demand, segmenting audiences, and optimizing spend, become the analytical backbone of how they operate. When your work is right, it drives measurable outcomes. When it's wrong, someone notices. That accountability is part of what makes this role interesting.
You'll also contribute to building the analytics capabilities OneMagnify delivers at scale. That means writing code and documentation that others can reproduce, maintain, and extend. Shipping a model is the beginning, not the end. Cross-functional collaboration with engineering, strategy, and delivery teams is part of the daily rhythm, and your ability to translate between technical and business contexts will be used constantly.
The work spans industries and problem types (automotive, retail, financial services, and more) so you'll develop breadth alongside depth. You'll rarely work on the same type of problem twice in a row.
What You'll Do
Build and validate analytical models
  • Design, deploy, and monitor models including forecasting, classification, regression, and segmentation
  • Conduct A/B testing and causal analyses with rigorous experimental design and clear documentation
  • Develop optimization solutions (linear, mixed-integer, multi-objective) and ensure reproducibility across the full model lifecycle

Own data integration and quality
  • Integrate data from multiple sources and develop data-quality reporting that surfaces issues before they become client problems
  • Conduct root-cause analysis on data anomalies and validate database changes prior to release
  • Use Databricks for large-scale data processing and machine learning workflows

Translate requirements into technical solutions
  • Partner with business and engineering teams to elicit requirements, define business rules, and turn them into technical specifications
  • Document solutions clearly enough that someone else can maintain and extend your work
  • Ensure alignment between what clients ask for and what gets built

Communicate findings to varied audiences
  • Synthesize and present analytical findings to internal and external stakeholders, including executive-level audiences, with the judgment to handle complex or sensitive inquiries with care
  • Build metrics and KPI reports that inform real business decisions, not just dashboards that get ignored
  • Prepare visualizations in Tableau and Power BI that make complex outputs accessible

Support collaborative development
  • Use Git/GitLab for version control, reproducibility, and collaborative code development
  • Collaborate with engineering teams to implement MLOps practices including model deployment, monitoring, and end-to-end lifecycle management using tools such as MLflow
  • Adhere to data governance, privacy, and compliance standards across all work

What You'll Need
  • BA/BS in Computer Science, Statistics, Mathematics, MIS, Marketing Research, or a related quantitative field - or equivalent practical experience
  • 2-5+ years of hands-on analytics including predictive modeling, A/B testing, and optimization
  • Advanced SQL and Python; strong ability to query, manipulate, and interpret data from databases and data warehouses
  • Hands-on experience with Databricks for large-scale data processing and machine learning workflows
  • Proficiency with Tableau and/or Power BI for visualization and reporting
  • Experience with Git/GitLab for version control and collaborative development
  • Strong Excel and PowerPoint skills
  • Proven ability to present analyses to management and collaborate with both business and technical stakeholders
  • Experience diagnosing and resolving data-quality issues across multiple platforms
  • Understanding of data governance, privacy, and compliance standards
  • Familiarity with Master Data Management (MDM) concepts and how they apply to data quality and integration

Future-Ready Skills (Nice to Have)
  • Proficiency with SAS or R in an applied analytics environment
  • Familiarity with automotive or VIN data and complex industry-specific data structures
  • Exposure to AI-enabled analytics workflows or automation within a data science context
  • Experience working in integrated marketing, consulting, or digital services environments where analytics supports client-facing delivery

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