Data Scientist
Dearborn, MI · Remote
... ontology-informed modeling approaches. The candidate will help ensure that analytical outputs are ... Bachelor's degree in Data Science, Engineering, Mathematics, Computer Science, Operations Research ...
Data Scientist
Dearborn, MI · Remote
... ontology-informed modeling approaches. The candidate will help ensure that analytical outputs are ... Bachelor's degree in Data Science, Engineering, Mathematics, Computer Science, Operations Research ...
Remote Ontology Engineer information
What is a remote ontology engineer?
A Remote Ontology Engineer is a professional who designs, develops, and maintains ontologies—structured frameworks for organizing information—while working from a remote location. They use their expertise in knowledge representation, semantic web technologies, and data modeling to ensure that information systems can interpret and connect data effectively. Their work is crucial in fields like artificial intelligence, data integration, and information retrieval, as they help systems 'understand' relationships between different pieces of data. Remote Ontology Engineers often collaborate with developers, data scientists, and domain experts using online tools and communication platforms.
How does a remote ontology engineer typically collaborate with cross-functional teams while working off-site?
As a Remote Ontology Engineer, you will frequently collaborate with data scientists, software developers, and subject matter experts through virtual meetings, shared documentation, and project management tools. Effective communication and proactive documentation are key, as you'll often need to clarify domain concepts and ensure semantic consistency across distributed teams. Many organizations use agile methodologies, so you can expect regular stand-ups and sprint planning sessions to stay aligned on project goals and deliverables. Building strong relationships remotely requires initiative, responsiveness, and a willingness to leverage digital collaboration platforms.
What are the key skills and qualifications needed to thrive as a remote ontology engineer, and why are they important?
To thrive as a Remote Ontology Engineer, you need a strong background in computer science, knowledge representation, and formal logic, typically supported by a relevant degree and experience in semantic technologies. Familiarity with ontology development tools (such as Protégé), semantic web standards (like OWL and RDF), and querying languages (SPARQL) is essential. Excellent problem-solving, communication, and self-motivation skills help you collaborate effectively in distributed teams and translate complex domain knowledge into structured ontologies. These skills are crucial for building robust, interoperable knowledge models that support data integration and intelligent applications across industries.
What is the difference between Remote Ontology Engineer vs Data Scientist?
| Aspect | Remote Ontology Engineer | Data Scientist |
|---|---|---|
| Required Credentials | Master's in Computer Science, Knowledge Engineering, or related fields; certifications in ontology modeling | Degree in Data Science, Statistics, or related; certifications in data analysis or machine learning |
| Work Environment | Collaborates with AI, semantic web, and knowledge management teams; often in tech or research industries | Works with data analysis, modeling, and visualization teams; across various industries including tech, finance, and healthcare |
| Employer & Industry Usage | Used in AI, semantic web, and knowledge-based systems | Applied in analytics, predictive modeling, and business intelligence |
While both roles require technical expertise and involve working with complex data, Remote Ontology Engineers focus on developing and managing ontologies for knowledge representation, whereas Data Scientists analyze data to extract insights. The roles often overlap in tech environments but serve different core functions.
What are the most commonly searched types of Ontology Engineer jobs in Michigan?
The most popular types of Ontology Engineer jobs in Michigan are:
What are popular job titles related to Remote Ontology Engineer jobs in Michigan?
For Remote Ontology Engineer jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Remote Ontology Engineer jobs in Michigan look for?
The top searched job categories for Remote Ontology Engineer jobs in Michigan are:
What cities in Michigan are hiring for Remote Ontology Engineer jobs?
Cities in Michigan with the most Remote Ontology Engineer job openings:
Full-time
Medical, Dental, Vision, Life, PTO
Re-posted 15 days ago
Ford Motor Company rating
7.6
Based on 525 frontline employees who took The Breakroom Quiz
13th 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.
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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.
What Ford Motor Company employees say
Pay
Benefits
Hours and flexibility
Workplace
Get the full story on Breakroom
About Ford Motor Company
Sourced by ZipRecruiter
Industry
Motor vehicle manufacturing and trucking
Company size
10,000+ Employees
Headquarters location
Dearborn, MI, US