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Remote Data Analyst Logistics Jobs in Michigan (NOW HIRING)

Ford Motor Company

Data Scientist

Dearborn, MI · Remote

Integrating heterogeneous enterprise datasets into structured, analysis-ready pipelines using ... Benefit Summary This role is remote but if you live within 50 miles within Dearborn, MI, you will ...

Select Minds LLC

Facets Analyst

Lansing, MI · On-site +1

$95K - $98K/yr

Remote - United States Work Hours: EST hours Employment: Full-Time Geographic Restrictions ... Perform data analysis and validation using Oracle SQL/PL/SQL. * Support production issue analysis ...

Workiva

$22/hr

Analyze data to drive decision-making on new features of Wdesk * Suggest new product development ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Workiva

$22/hr

Analyze data to drive decision-making on new features of Wdesk * Suggest new product development ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Workiva

$22/hr

Analyze data to drive decision-making on new features of Wdesk * Suggest new product development ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Workiva

$22/hr

Analyze data to drive decision-making on new features of Wdesk * Suggest new product development ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Workiva

$22/hr

Analyze data to drive decision-making on new features of Wdesk * Suggest new product development ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Workiva

$22/hr

Analyze data to drive decision-making on new features of Wdesk * Suggest new product development ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Workiva

Spring 2027 Intern - Data Analytics

Lansing, MI · On-site +1

$22/hr

Analyze data to drive decision-making on new features of Wdesk * Suggest new product development ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Workiva

$22/hr

Analyze data to drive decision-making on new features of Wdesk * Suggest new product development ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Workiva

$22/hr

Analyze data to drive decision-making on new features of Wdesk * Suggest new product development ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Workiva

Spring 2027 Intern - Data Analytics

Detroit, MI · On-site +1

$22/hr

Analyze data to drive decision-making on new features of Wdesk * Suggest new product development ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

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All JobsData Analyst Logistics JobsRemote Data Analyst Logistics JobsRemote Data Analyst Logistics Jobs in Michigan

Remote Data Analyst Logistics information

What does a remote data analyst in logistics do?

A Remote Data Analyst in Logistics is responsible for collecting, analyzing, and interpreting data related to supply chain operations, shipping, inventory, and transportation. They use various analytical tools to identify trends, optimize processes, and help their organization make data-driven decisions to improve efficiency and reduce costs. Working remotely, they collaborate with teams using digital communication tools and often create reports or dashboards to present their findings to stakeholders.

What are the key skills and qualifications needed to thrive as a remote data analyst in logistics?

To thrive as a Remote Data Analyst in Logistics, you need strong analytical skills, expertise in data modeling, and a background in logistics or supply chain management, often supported by a relevant degree. Proficiency in tools such as SQL, Excel, Tableau, and experience with logistics management systems or ERP software is typically required. Excellent problem-solving, attention to detail, and clear communication skills help you work independently and convey insights to cross-functional teams. These capabilities are crucial for optimizing supply chain operations, driving efficiency, and supporting data-driven decision-making in a remote environment.

How does a remote data analyst in logistics typically collaborate with cross-functional teams to optimize supply chain processes?

As a Remote Data Analyst in logistics, you will frequently collaborate with supply chain managers, IT specialists, and operations teams through virtual meetings and shared data platforms. Your role involves interpreting large datasets to identify trends, inefficiencies, and improvement opportunities, and then communicating actionable insights to stakeholders. Regular collaboration ensures data-driven decisions are aligned with organizational goals, and you may also assist in developing dashboards or reports for ongoing performance monitoring. This teamwork is essential in optimizing inventory management, transportation routes, and overall supply chain effectiveness.

What is the difference between Remote Data Analyst Logistics vs Remote Data Analyst Supply Chain?

AspectRemote Data Analyst LogisticsRemote Data Analyst Supply Chain
Required CredentialsBachelor's in Logistics, Supply Chain, or related field; data analysis certificationsBachelor's in Supply Chain Management, Business Analytics, or related; data analysis certifications
Work EnvironmentLogistics companies, transportation firms, warehousingManufacturers, retailers, distribution centers
Employer & Industry UsageLogistics and freight companiesSupply chain and procurement sectors
Search & Comparison IntentFocus on logistics operations and transportation dataFocus on overall supply chain processes and procurement data

Remote Data Analyst Logistics primarily focuses on analyzing transportation, warehousing, and logistics operations, while Remote Data Analyst Supply Chain covers broader supply chain processes including procurement and inventory management. Both roles require similar skills and certifications but differ in industry focus and work environment.

Are remote data analyst logistics in high demand?

Remote data analyst roles in logistics are in high demand due to the increasing reliance on data-driven decision making and supply chain optimization. Skills in data analysis tools like Excel, SQL, and visualization software are highly valued, and the role often offers flexible schedules and remote work options.

Can I work in logistics remotely?

Remote data analyst roles in logistics are increasingly available, especially with the use of data analysis tools like Excel, SQL, and visualization software. These positions often require strong analytical skills and may involve collaboration via online platforms, making remote work feasible for qualified candidates.

Is it possible to work remotely as a remote data analyst logistics?

Remote data analyst logistics roles are increasingly available, allowing professionals to analyze supply chain and transportation data from home. These positions often require proficiency with data analysis tools, such as Excel or SQL, and strong communication skills. Employers may specify remote work options based on company policies and the nature of the logistics tasks involved.

What are popular job titles related to Remote Data Analyst Logistics jobs in Michigan?

For Remote Data Analyst Logistics jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Remote Data Analyst Logistics jobs in Michigan look for?

The top searched job categories for Remote Data Analyst Logistics jobs in Michigan are:

What cities in Michigan are hiring for Remote Data Analyst Logistics jobs?

Cities in Michigan with the most Remote Data Analyst Logistics job openings:

Remote Data Analyst Logistics jobs near you
Infographic showing various Remote Data Analyst Logistics job openings in Michigan as of June 2026, with employment types broken down into 78% Full Time, 20% Part Time, and 2% Contract. Highlights an 69% Physical, 1% Hybrid, and 30% Remote job distribution.

Data Scientist

Ford Motor Company

Dearborn, MI • Remote

Full-time

Medical, Dental, Vision, Life, PTO

Re-posted 24 days ago

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

The Senior Data Scientist will design and implement advanced systems that support cross-domain manufacturing analytics. This role operates at the intersection of optimization, enterprise data integration, and applied analytics to enable data-driven decision-making across complex business workflows.

Key responsibilities include:

  • Developing and maintaining Python-based optimization models to support demand elasticity, production planning, and constraint-based decision frameworks.

  • Integrating heterogeneous enterprise datasets into structured, analysis-ready pipelines using BigQuery, GCS, and Python.

  • Performing data reconciliation, fuzzy matching, and standardization across inconsistent source systems to ensure data quality and analytical integrity.

  • Designing and deploying lightweight internal applications (e.g., Dash-based tools) and contributing to containerized deployments to enable business-facing access to decision models.

  • Collaborating with cross-functional stakeholders to translate business questions into optimization and analytical frameworks.

In addition, this role will contribute to the development of semantically aligned data structures by supporting feature definition consistency, cross-system mapping, and ontology-informed modeling approaches. The candidate will help ensure that analytical outputs are built on clearly defined entities, relationships, and assumptions to enable scalable reasoning and reuse across domains.

The ideal candidate combines strong technical modeling capability with practical enterprise data engineering experience and the ability to operate effectively in ambiguous, cross-functional environments.

  • Bachelor's degree in Data Science, Engineering, Mathematics, Computer Science, Operations Research, or equivalent field.

  • 3+ years of experience developing analytical or optimization models in Python.

  • Experience building and maintaining data pipelines using SQL and cloud-based data platforms (e.g., BigQuery, GCS).

  • Strong proficiency in Python for data analysis and modeling (e.g., pandas, NumPy, Pyomo or similar optimization libraries).

  • Experience integrating and standardizing heterogeneous enterprise datasets.

  • Familiarity with containerization concepts (e.g., Docker) and deploying lightweight applications or services in a cloud environment.

  • Ability to translate business problems into structured analytical frameworks.

  • Strong written and verbal communication skills with experience working cross-functionally.

You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!
As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder...or all of the above? No matter what you choose, we offer a work life that works for you, including:
Immediate medical, dental, vision and prescription drug coverage
Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care and more
Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more
Vehicle discount program for employees and family members and management leases
Tuition assistance
Established and active employee resource groups
Paid time off for individual and team community service
A generous schedule of paid holidays, including the week between Christmas and New Year's Day
Paid time off and the option to purchase additional vacation time.
 
For a detailed look at our benefits, click here: Benefit Summary
 
 
This role is remote but if you live within 50 miles within Dearborn, MI, you will be required on-site 4x a week.
 
*Visa Sponsorship IS provided for this specific role*
*Relocation assistance IS provided for this specific role*
 
Candidates for positions with Ford Motor Company must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire.
We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status. In the United States, If you need a reasonable accommodation for the online application process due to a disability, please call 1-888-336-0660.
 
#LI-Remote
#LI-DS2 
 
SG7-8

  • Design, develop, and maintain Python-based optimization models to support demand elasticity, production planning, and constraint-based decision systems.

  • Translate complex business problems into structured analytical and optimization frameworks.

  • Build and maintain data pipelines using BigQuery, GCS, and Python to integrate heterogeneous enterprise data sources.

  • Perform data reconciliation, fuzzy matching, and standardization across inconsistent datasets to ensure analytical integrity.

  • Develop lightweight internal applications (e.g., Dash or streamlit) to operationalize analytical outputs for business users.

  • Contribute to containerized deployments to support scalable and maintainable delivery of decision tools.

  • Partner with cross-functional stakeholders to define requirements and validate outputs.

  • Support semantic alignment across systems by contributing to feature definition consistency, cross-system mapping, and ontology-informed data structures.

  • Document modeling assumptions, data transformations, and system dependencies to enable reproducibility and reuse.

  • Continuously improve model performance, data quality, and deployment efficiency across decision systems.

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