Data Scientist
Dearborn, MI · Remote
Bachelor's degree in Data Science, Engineering, Mathematics, Computer Science, Operations Research ... Remote #LI-DS2 SG7-8 * Design, develop, and maintain Python-based optimization models to support ...
Data Scientist
Dearborn, MI · Remote
Bachelor's degree in Data Science, Engineering, Mathematics, Computer Science, Operations Research ... Remote #LI-DS2 SG7-8 * Design, develop, and maintain Python-based optimization models to support ...
Principal Credit Risk & Pricing Analyst
Lansing, MI · On-site +1
$143K - $180K/yr
Design statistical and mathematical models for reporting and predictive analytics. * Develop ... day remote Pay Transparency The salary range for this position is $143,705 - $180,000 per year ...
Principal Credit Risk & Pricing Analyst
Lansing, MI · On-site +1
$143K - $180K/yr
Design statistical and mathematical models for reporting and predictive analytics. * Develop ... day remote Pay Transparency The salary range for this position is $143,705 - $180,000 per year ...
Bachelor's degree in Computer Science, Mathematics, Physics, or equivalent senior-level industry ... Experience with remote attestation, secure enclaves, and hardware-backed key protection in cloud or ...
Bachelor's degree in Computer Science, Mathematics, Physics, or equivalent senior-level industry ... Experience with remote attestation, secure enclaves, and hardware-backed key protection in cloud or ...
Mathematical Optimization Remote information
What are some common challenges faced by professionals in remote mathematical optimization roles, and how can they be addressed?
Remote mathematical optimization professionals often encounter challenges such as limited real-time collaboration with team members, managing complex problem-solving tasks independently, and ensuring effective communication of technical findings to non-technical stakeholders. To address these challenges, it's helpful to establish regular virtual meetings, use collaborative tools for sharing code and results, and develop clear documentation. Additionally, proactively seeking feedback and staying engaged with the broader team can help maintain alignment and foster innovation.
What is a Mathematical Optimization Remote job?
A Mathematical Optimization Remote job involves using mathematical techniques and algorithms to solve optimization problems, such as maximizing efficiency or minimizing costs, while working from a remote location. Professionals in this field apply optimization theory, modeling, and computational methods to real-world problems in industries like logistics, finance, engineering, and data science. Remote roles allow for flexibility, enabling collaboration with teams and clients online while leveraging specialized software and programming languages such as Python, MATLAB, or R.
What is the difference between Mathematical Optimization Remote vs Data Analyst Remote?
| Aspect | Mathematical Optimization Remote | Data Analyst Remote |
|---|---|---|
| Required Credentials | Degree in Mathematics, Operations Research, or related field; proficiency in optimization software | Degree in Statistics, Mathematics, or related field; proficiency in data analysis tools |
| Work Environment | Remote, often collaborative with teams on complex modeling projects | Remote, focused on data collection, visualization, and reporting |
| Industry Usage | Finance, logistics, supply chain, tech companies | Marketing, finance, healthcare, tech companies |
| Common Search/Comparison | Yes | No |
Mathematical Optimization Remote specialists focus on developing algorithms to optimize processes and decision-making, often requiring advanced mathematical skills. Data Analysts Remote interpret data to provide insights, using statistical tools. While both roles are remote and involve data, they differ in technical focus and industry applications.
What are the key skills and qualifications needed to thrive as a Mathematical Optimization Specialist working remotely, and why are they important?
To thrive as a Mathematical Optimization Specialist in a remote setting, you need a strong background in mathematics, operations research, or computer science, often supported by an advanced degree. Proficiency with optimization software (such as Gurobi, CPLEX, or MATLAB), programming languages like Python or R, and familiarity with cloud-based collaboration tools is typically required. Excellent problem-solving abilities, self-motivation, and clear communication skills help you stand out when collaborating with distributed teams and stakeholders. These skills and qualities are crucial for efficiently developing, implementing, and explaining optimization solutions in a remote work environment.
What are the most commonly searched types of Mathematical Optimization jobs in Michigan? The most popular types of Mathematical Optimization jobs in Michigan are:
What are popular job titles related to Mathematical Optimization Remote jobs in Michigan? For Mathematical Optimization Remote jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Mathematical Optimization Remote jobs in Michigan look for? The top searched job categories for Mathematical Optimization Remote jobs in Michigan are:
What cities in Michigan are hiring for Mathematical Optimization Remote jobs? Cities in Michigan with the most Mathematical Optimization Remote job openings:
Full-time
Medical, Dental, Vision, Life, PTO
Posted 20 days ago
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.
About Ford
Sourced by ZipRecruiter
At Ford Motor Company, we believe freedom of movement drives human progress. With our incredible plans for the future of mobility, we have a wide variety of opportunities for you to accelerate your career and help us define tomorrow's transportation.
Industry
Civil engineering construction
Company size
51 - 200 Employees
Headquarters location
Doral, FL, US
Year founded
1982