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What is mathematical optimization in operations research?

Mathematical Optimization in Operations Research is the process of finding the best solution from a set of feasible options, subject to constraints, by maximizing or minimizing an objective function. It involves formulating real-world problems mathematically and using algorithms to identify optimal or near-optimal solutions. This field is widely applied in logistics, finance, manufacturing, and other industries to improve efficiency and reduce costs. Professionals use techniques such as linear programming, integer programming, and nonlinear optimization to solve complex decision-making problems.

What are some typical challenges faced by professionals in mathematical optimization operations research, and how can they be addressed?

Professionals in Mathematical Optimization Operations Research often encounter challenges such as dealing with large-scale, complex datasets and ensuring that models are both accurate and computationally efficient. Balancing the precision of theoretical models with the practical limitations of real-world data and time constraints is a common hurdle. Collaboration with domain experts and iterative model refinement are essential strategies to address these issues. Additionally, clear communication of technical results to non-technical stakeholders is crucial for successful project implementation.

What are the key skills and qualifications needed to thrive as a mathematical optimization operations research analyst, and why are they important?

To excel as a Mathematical Optimization Operations Research Analyst, you need advanced skills in mathematics, statistics, and analytical modeling, usually supported by a degree in operations research, applied mathematics, or a related field. Familiarity with optimization software (such as CPLEX or Gurobi), programming languages like Python or R, and data analysis tools is typically required. Strong problem-solving abilities, critical thinking, and effective communication help you translate complex data into actionable business solutions. These competencies are crucial for delivering efficient, data-driven strategies that optimize organizational performance and decision-making.

What are popular job titles related to Mathematical Optimization Operations Research jobs in Illinois?

For Mathematical Optimization Operations Research jobs in Illinois, the most frequently searched job titles are:

What job categories do people searching Mathematical Optimization Operations Research jobs in Illinois look for?

The top searched job categories for Mathematical Optimization Operations Research jobs in Illinois are:

What cities in Illinois are hiring for Mathematical Optimization Operations Research jobs?

Cities in Illinois with the most Mathematical Optimization Operations Research job openings:

Mathematical Optimization Operations Research jobs near you
Infographic showing various Mathematical Optimization Operations Research job openings in Illinois as of August 2026, with employment types broken down into 67% Full Time, 30% Part Time, 1% Temporary, 1% Contract, and 1% Nights. Highlights an 93% Physical, 3% Hybrid, and 4% Remote job distribution.

Operations Research & Applied AI Engineer

Roadrunner

Downers Grove, IL • On-site

$69K - $93K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 7 days ago

Roadrunner Freight rating

5.8

Company rating: 5.8 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

Job description

We are seeking an experienced Operations Research & Applied AI Engineer to build and grow our advanced analytics capabilities. This role combines mathematical optimization with applied artificial intelligence, and it carries responsibility both for maintaining and improving the systems we have today and for identifying, designing, and delivering the ones we do not yet have.
The ideal candidate is a hands-on practitioner with genuine depth in optimization and practical experience putting AI applications into production. We care about demonstrated capability rather than credentials, and substantial hands-on experience can stand in place of an advanced degree. This is a builder's role. We expect the person in this seat to look at how the business plans, prices, and moves freight, recognize where a decision is being made by intuition that could be made by a model, and make the case for solving it. Over time, the scope of this position is expected to expand well beyond its starting systems as new opportunities are identified and delivered.
This role requires someone who can reason rigorously about model design and solution quality, insist on measurable evaluation before anything reaches production, and then explain the resulting business trade-offs to the leaders who act on them. Experience in the transportation and logistics industry is preferred, as the role involves working with data related to network and capacity planning, service performance, fleet and driver operations, and freight documentation.What you'll do
1. Optimization & Operations Research
  • Design, build, maintain, and improve mathematical optimization models supporting network planning, capacity and resource allocation, routing, and related operational decisions.
  • Formulate and solve large-scale mixed-integer and network flow problems and select appropriate exact or heuristic methods based on problem structure and the time available to solve.
  • Establish and maintain rigorous solution quality measurement, including derived bounds, so that the value of every model change can be demonstrated rather than asserted.
  • Translate model parameters, penalties, and constraints into the business trade-offs they represent, and adjust them in partnership with operational stakeholders.

2. Applied AI Solution Development
  • Design and deliver applied AI applications that automate manual processes, extract structured data from unstructured sources, and support operational decision-making.
  • Move AI solutions from prototype to production, including hosting and scheduling, continuous integration, versioning of prompts and output schemas, structured logging, monitoring, and human review paths for low-confidence output.
  • Design and maintain evaluation frameworks for AI output, including curated ground-truth sets, accuracy measurement, and regression gates that determine objectively whether a change improved results.
  • Stay current with developments in applied AI and optimization, and assess which are worth adopting in an operational environment.

3. Opportunity Identification & Solution Design
  • Assess business processes across operations, pricing, sales, and finance to identify opportunities where optimization or AI would deliver measurable value.
  • Build the business case for new initiatives, including expected impact, feasibility, data requirements, and level of effort, and present recommendations to leadership.
  • Prototype quickly to test whether an approach is viable, and be equally willing to recommend against building something when the evidence does not support it.
  • Scale successful prototypes into supported production systems with documented design decisions and a defined owner.

4. Model Validation & Benchmarking
  • Benchmark system output against actual business results to confirm that modeled improvements translate into realized ones.
  • Distinguish genuine improvement from run-to-run variation, and document negative results as rigorously as positive ones so that approaches are not re-attempted without cause.
  • Build and maintain the testing and validation infrastructure that keeps analytical systems correct as they change.

5. Stakeholder Engagement & Business Partnership
  • Partner with Operations, Pricing, Sales, and Executive Leadership to understand how work is actually performed, and incorporate that operational reality into model design.
  • Present modeling results, recommendations, and trade-offs clearly to both technical and non-technical audiences.
  • Service ongoing requests for scenario analysis and decision support, including the projected cost and service impact of proposed operational changes.
  • Work with security, technology, and business stakeholders to resolve the approvals, data access, and policy decisions required to bring new systems into production use.
  • Collaborate closely with data engineering and business intelligence partners on shared data dependencies and downstream reporting, and provide guidance and mentorship to team members on analytical and modeling best practices.

What you bring
  • Bachelor's degree in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, Statistics, or a related quantitative field (or equivalent experience).
  • 5+ years of experience applying mathematical optimization to production business problems, with demonstrated ability to connect model design to operational outcomes. An advanced degree in a quantitative field may substitute for a portion of this experience.
  • Strong mixed-integer programming proficiency: ability to formulate, debug, and defend optimization models; interpret LP relaxations, duality, and solver gaps; and diagnose why a model fails to solve within acceptable limits. Hands-on experience with at least one solver such as SCIP, Gurobi, or CPLEX.
  • Demonstrated ability to design heuristic and metaheuristic methods rather than only apply them, including selecting approaches appropriate to a problem's structure.
  • Working knowledge of production AI applications built on large language models, including hosted model APIs, structured and schema-constrained output, and failure handling against a non-deterministic service.
  • Demonstrated evaluation methodology for AI or model output, including ground-truth set construction, accuracy measurement, and making a stochastic pipeline regression-testable.
  • Strong Python proficiency: typed, tested, packaged production code, with attention to algorithmic performance.
  • SQL proficiency sufficient to work with relational data sources and to design and maintain output schemas.
  • Strong analytical and critical thinking skills, with a track record of measuring results honestly and distinguishing improvement from noise.
  • Demonstrated ability to identify opportunities independently and advocate for them, rather than working solely from an assigned backlog.
  • Excellent verbal and written communication skills, with the ability to present findings and business trade-offs clearly to both technical and non-technical stakeholders.
  • Ability to manage multiple priorities and work independently in a fast-paced, results-driven environment.

Preferred Qualifications
  • Advanced degree in Operations Research, Industrial Engineering, Applied Mathematics, or a related quantitative field.
  • Experience in the transportation, logistics, or supply chain industry, particularly network design, load planning, capacity planning, empty repositioning, or driver and crew planning.
  • Familiarity with Power BI, DAX, SSAS, SSIS, and other data engineering and reporting tools
  • Familiarity with freight operations concepts such as service standards, hub and terminal operations, cube-versus-weight capacity, and equipment constraints.
  • Experience with vision or multimodal models applied to document processing.
  • Experience with bin packing, container loading, or scheduling problems.
  • Experience with Azure OpenAI or comparable enterprise AI platform services.
  • Experience packaging and deploying analytical applications for unattended production execution.
  • Background in statistics, simulation, or forecasting.

How you operate
  • You think in systems, not tasks.
  • You measure outcomes, not activity.
  • You challenge assumptions with data and evidence.
  • You balance innovation with operational discipline.
  • You move quickly without compromising reliability or quality.
  • You can simplify complex concepts for diverse audiences.
  • You make decisions with both analytical rigor and business context.
  • You are comfortable operating in ambiguity while creating clarity for others.
  • You prioritize long-term scalability over short-term fixes.
  • You take ownership from problem identification through production adoption.
  • You seek measurable impact and objectively evaluate results.
  • You build trust through transparency, consistency, and execution.

Compensation & Setup
  • Base salary: $100,000 to $120,000 per year
  • Location: Hybrid | Downers Grove, IL
  • Benefits: Full benefits package including medical, dental, vision, 401(k), and PTO.

Physical Demands and Work Environment
The physical demands and work environment described here are representative of those an employee encounters while performing the essential functions of this position. Reasonable accommodations may be made to enable qualified individuals with disabilities to perform the essential functions.
Physical Demands
  • Sedentary physical activity performing non-strenuous daily activities of an administrative nature.
  • While performing the duties of the job, the employee is regularly required to sit, walk, stand, reach/handle items, work with the fingers, and talk and hear others in conversations via the phone or in person.

Work Environment
  • The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job.
  • The noise level in the work environment is usually moderate.

* The above statements reflect the general details necessary to describe the principal functions of the position and are not intended to be all inclusive. The position and any of the requirements listed above are subject to change at any time according to the changing needs of the company.
* Roadrunner is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind.
* We will not accept unsolicited candidates from external recruiters or recruiting agencies. Thank you!
#LI-HybridDowners Grove, IL
About Roadrunner
Roadrunner is for ambitious, smart people who excel at execution over talking about it, and who would rather invent the next standard in freight than accept the status quo.
We are looking for the Best of the Best. Action driven leaders who want to be part of real change and help design the future of LTL in the U.S. This is a place where high performers can grow, influence outcomes, and make an impact while working directly with executives and smart people from across industries.
We bring a winner mindset. We take ownership, raise the bar, and measure ourselves by results. We Run Safe. We Run Smart. We Run Together. These principles create an environment of high standards, clear ownership, and direct collaboration. We trust data over intuition, move with urgency, and hold each other accountable because winning requires it.
Roadrunner exists to prove that LTL can be better than the industry has settled for. To be the best means we need to think bigger, look outside the box, and question every assumption: too many handoffs, limited visibility, and the quiet belief that "this is just how it works." We rejected that story. We built a proprietary Smart Network™ for direct, long haul, metro to metro service that delivers fewer touches, faster transit, real time visibility, and genuine accountability. We are the most tech forward company in LTL, and we are not finished widening the gap.
The foundation is already strong. Recognized as one of Built In Chicago's Best Large Places to Work. Earning top marks for improvement, quality, and service. The real opportunity is still ahead: helping invent what comes next.
If you want to be evaluated among the Best of the Best and help set the new standard in LTL, we should talk.

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