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Mathematical Optimization Remote Jobs in Michigan

Senior Staff Data Engineer

Portage, MI · On-site +1

$153K - $255K/yr

Remote Join a team focused on building scalable, enterprise-grade data platforms that support ... Drive platform decisions related to performance optimization, scalability, and cost efficiency.

Showing results 21-26

Mathematical Optimization Remote information

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 are the key skills and qualifications needed to thrive as a mathematical optimization specialist working remotely?

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 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 the difference between Mathematical Optimization Remote vs Data Analyst Remote?

AspectMathematical Optimization RemoteData Analyst Remote
Required CredentialsDegree in Mathematics, Operations Research, or related field; proficiency in optimization softwareDegree in Statistics, Mathematics, or related field; proficiency in data analysis tools
Work EnvironmentRemote, often collaborative with teams on complex modeling projectsRemote, focused on data collection, visualization, and reporting
Industry UsageFinance, logistics, supply chain, tech companiesMarketing, finance, healthcare, tech companies
Common Search/ComparisonYesNo

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 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:

Physics Content Evaluator (LaTeX/Python)

micro1 AI

Detroit, MI • On-site, Remote

$80 - $150/hr

Part-time

Posted 16 days ago


Job description

Role Title: Physics Expert (Postdoc / Junior professor)


Role Type: Contractor


Location: Remote (US, Canada, UK focused)


micro1 is engaging Physics Experts (Postdoc / Junior professor) to participate in a high-impact project supporting a customer in the science and technology sector. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Critically evaluate and review physics solutions, mathematical derivations, and theoretical arguments generated by researchers or AI platforms.
  2. Detect errors, unjustified steps, missing assumptions, dimensional inconsistencies, and weaknesses in logic or methodology.
  3. Delineate between substantive scientific issues and stylistic or cosmetic matters, providing technically precise written feedback.
  4. Articulate and document the reasoning behind any identified flaws, ensuring actionable guidance for improvement.
  5. Recognize when correct reasoning can be optimized, and offer suggestions to sharpen or clarify the argument.
  6. Utilize LaTeX, SymPy, Python, and Jupyter to independently verify or counter-check scientific claims as appropriate.
  7. Deliver structured feedback designed to support iterative enhancement of submitted work and project outcomes.


Preferred Qualifications

  1. PhD in physics and an active record of independent research within a specialized subfield (e.g., High Energy/Mathematical Physics, Biophysics/Statistical Physics, Condensed Matter, AMO/Quantum Optics, Gravitation/Cosmology, Quantum Information, or Optical Materials).
  2. Experience as a postdoctoral researcher, research fellow, junior/assistant professor, or senior research scientist.
  3. Recent (last ~5 years) representative publications in the relevant subfield, with arXiv or DOI links.
  4. Advanced proficiency with LaTeX, SymPy, Python, and Jupyter for theoretical modeling and computational validation.
  5. Demonstrated skill in reviewing the work of others—through peer review, supervision, dissertation committees, or group seminars.
  6. Exceptional written communication skills with the ability to convey nuanced, constructive feedback with technical rigor.
  7. Reliable access to high-speed internet and a computer suitable for rigorous technical work.