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Data Analytics Director Jobs in Michigan (NOW HIRING)

Overview Technomics is a growing employee-owned, decision analytics company that provides ... Direct Palantir Foundry experience is preferred but not required. Responsibilities and ...

Overview Technomics is a growing employee-owned, decision analytics company that provides ... Direct Palantir Foundry experience is preferred but not required. Responsibilities and ...

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Data Analytics Director information

See Michigan salary details

$61.9K

$137.8K

$213.1K

How much do data analytics director jobs pay per year?

As of Sep 5, 2026, the average yearly pay for data analytics director in Michigan is $137,813.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,600.00 and $156,900.00 per year, depending on experience, location, and employer.

What does a Data Analytics Director do?

A Data Analytics Director is responsible for overseeing the data analytics department within an organization. They lead teams that collect, process, and interpret large sets of data to provide actionable insights for business decision-making. This role involves developing data strategies, implementing analytical tools and techniques, and ensuring data quality and security. The Data Analytics Director also collaborates with other departments to align analytics initiatives with organizational goals and drive data-driven growth.

What are the key skills and qualifications needed to thrive as a Data Analytics Director?

To thrive as a Data Analytics Director, you need advanced expertise in data analysis, statistical modeling, and business intelligence, typically supported by a relevant degree and significant experience in analytics leadership. Familiarity with tools such as SQL, Python, R, and data visualization platforms like Tableau or Power BI, along with knowledge of data governance and cloud technologies, is essential. Exceptional leadership, strategic thinking, and communication skills help drive cross-functional collaboration and translate data insights into business value. These competencies are crucial for guiding analytic strategy, ensuring data-driven decision-making, and maximizing organizational impact.

What are some common challenges faced by a Data Analytics Director when aligning analytics initiatives with business objectives?

A Data Analytics Director often encounters challenges in ensuring that analytics projects are closely aligned with the strategic goals of the organization. This includes bridging communication gaps between technical teams and business stakeholders, prioritizing projects with the highest business impact, and managing expectations regarding what data analytics can deliver. Additionally, it can be challenging to foster a data-driven culture across departments and to secure buy-in for data initiatives. Effective collaboration, clear communication, and a strong understanding of both analytics and business priorities are essential to overcome these hurdles.

What is the difference between Data Analytics Director vs Data Scientist?

AspectData Analytics DirectorData Scientist
Required CredentialsBachelor's or Master's in Data Science, Business, or related field; often requires leadership experienceBachelor's, Master's, or Ph.D. in Data Science, Statistics, or related field; technical expertise in modeling
Work EnvironmentLeadership role overseeing analytics teams, strategic planning, and project managementHands-on data analysis, model development, and algorithm implementation
Employer & Industry UsageUsed in corporate, finance, healthcare, and tech sectors for strategic decision-makingCommon in tech, research, and analytics firms for developing data models and insights

The main difference is that a Data Analytics Director focuses on leading analytics teams and strategic initiatives, while a Data Scientist is primarily involved in technical data modeling and analysis. Both roles require strong analytical skills, but the Director role emphasizes leadership and business strategy.

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

The most popular types of Data Analytics jobs in Michigan are:

What job categories do people searching Data Analytics Director jobs in Michigan look for?

The top searched job categories for Data Analytics Director jobs in Michigan are:

What cities in Michigan are hiring for Data Analytics Director jobs?

Cities in Michigan with the most Data Analytics Director job openings:

Infographic showing various Data Analytics Director job openings in Michigan as of August 2026, with employment types broken down into 33% Full Time, and 67% Contract. Highlights an 100% In-person job distribution, with an average salary of $137,813 per year, or $66.3 per hour.

Director, FCSD Data Analytics and Business Intelligence

Ford Motor Company

Allen Park, MI • On-site

Full-time

Re-posted 9 days ago


Key responsibilities

  • Lead the integration of data strategy, business intelligence, reporting, and customer experience analytics into a unified global team.

  • Build and manage a proactive team that provides deep, diagnostic, and predictive analytics to support business transformation and strategic decision-making.

  • Partner with business leaders to develop and automate enterprise KPIs, and deliver actionable insights through modern, AI-driven visualization platforms.


Ford Motor Company rating

7.6

Company rating: 7.6 out of 10

Based on 527 frontline employees who took The Breakroom Quiz

11th of 45 rated automakers


Job description

In this role, you will lead the strategic integration of several key functions-including data strategy, business intelligence, reporting, and customer experience analytics-into a unified, global team comprising both internal employees and external partners. Operating as a proactive service function, your organization will work in partnership with FCSD's business line leaders to directly support and accelerate their business results. This role is not about maintaining legacy processes or acting as a reactive "data vendor" that extracts raw files and distributes spreadsheets. Instead, you are tasked with architecting a modern, AI-first insights engine. You will build a highly proactive team that pushes our business leaders on their strategic thinking, challenges status-quo assumptions with deep, diagnostic and predictive analytics, and unlocks the critical insights needed to drive our business transformation.

Required Skills and Capabilities

  • Transformational Leadership & Vision: Exceptional capability to lead global, cross-functional teams through change, while maintaining a high-performing service identity.

  • AI-First Technical Vision: A forward-looking leader with a strong conceptual grasp of generative AI, large language models, automated machine learning, next-generation visualization platforms, and modern cloud data ecosystems. Must keep pace with new innovation and leverage the latest tooling and agents to rapidly prototype solutions and prove value before scaling.

  • Proactive Advisory & Influence: A track record of acting as a consultative partner rather than a transactional service provider; someone who can leverage data to challenge senior executive thinking and constructively shape business outcomes.

  • Collaborative Relationship Builder: Strong interpersonal skills with a proven track record of partnering across corporate skill teams, technology partners, and external organizations.

  • Resource Orchestration: Ability to manage complex, blended teams (internal and external vendors) and design high-performing operating models during organizational change.

  • Action & output oriented. Hands on keys builder that can roll up their sleeves alongside engineering teams

Minimum Qualifications:
  • Education: Bachelor's degree in Business Analytics, Data Science, Statistics, Economics, Engineering, Mathematics, Business, or a related field.

  • Experience:

    • Minimum of 10 years of progressive experience in business analytics, data strategy, business intelligence, or customer insights.

    • Minimum of 5 years of experience leading and developing global, multi-tiered, or cross-functional teams of 20+ professionals (including direct employees and vendors).

    • Experience leading a technology-focused team through transformation 

  • Technical & Platform Familiarity: Deep conceptual knowledge of modern cloud environments (e.g., Google Cloud Platform), automated BI semantic layers, advanced analytics workflows, and AI agents with experience successfully migrating legacy reporting into modernized platforms.

Preferred Qualifications:
  • Advanced Degree: Master's degree in Data Science, Mathematics, Engineering, or an MBA with an analytical focus.

  • Automotive or Aftersales Experience: Prior experience in dealership operations, automotive parts and service, or aftersales business dynamics.

  • Modern Methodology Certifications: Certified in modern, agile data product management, continuous delivery frameworks, or Lean methodologies.

1. Future-State Operating Model & Resource Integration

  • Design the Future Organization: Integrate diverse reporting and data/analytics teams into a global structure of 30+ professionals.

  • Orchestrate the Employee-Vendor Ecosystem: Efficiently manage a blended team of internal talent and external vendors. Ensure our partners effectively "run the railroads" so that internal teams can focus on high-value strategy and proactive insight generation.

  • Lead Cultural and Skill Transformation: Have a mindset of proactive, strategic advisory partner to FCSD business leaders, enabling the team to work seamlessly in modern, cloud-native, and AI-first environments.

2. Proactive Business Intelligence, Insights & Service Delivery

  • Support Business Line Results: Position the Data Analytics and Business Intelligence team as a premier service function, collaborating intimately with FCSD business line leaders to drive EBIT expansion and better operational execution.

  • Challenge the Status Quo: Shift the division away from, manual spreadsheet-sharing toward dynamic, predictive business intelligence. Empower your team to synthesize complex datasets and deliver sharp, actionable insights that proactively shape future business strategies.

  • Establish Dynamic Enterprise KPIs: Oversee the development and automation of next-generation performance metrics, utilizing AI-driven visualization to track and predict customer pay service, leads, wholesale, parts supply & logistic, network performance.

  • Own the Semantic Layer and Metric Governance: Reinforce centralized Business Rules to eliminate conflicting data across business units, ensuring a single version of truth.

3. Integrated Customer & Dealer Data Strategy

  • Consolidate Dealer & CX Data: Evolve the customer and dealer lifecycle by bringing Dealer Management System (DMS) datasets and Customer Experience (CX) survey metrics into a single, unified data strategy. 
  • Synthesize Voice of Customer (VoC) and industry data: Build cohesive feedback loops that make customer and dealer sentiment and industry benchmark insights highly visible and actionable from executive leadership to the dealership floor.
  • Continue Leadership in Data Integration: Define the long-term vision for dealer-partner data sharing, integration, and security, ensuring high-integrity, compliant pipelines feed the team's advanced analytics engines.

4. AI-First Analytics & Modern Tech Stack Evolution

  • Establish an AI-First Culture: Leverage AI to automate routine reporting, accelerate insight generation, and perform diagnostic modeling at scale.

  • Partner with Central Ford Tech teams: Collaborate closely with Ford's centralized data science and Enterprise Technology organizations to transition FCSD's data assets from legacy environments into modern, cloud-native architectures


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