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Linear Programming Analyst Jobs (NOW HIRING)

Data scientists work closely with data engineers, analysts, and business teams to design analytics ... Develop and validate models using techniques such as regression, optimization (linear programming ...

Practical experience using industry-standard Linear Programming software (Aspen PIMS, AVEVA Unified ... Experience in leveraging AI tools (Claude, Cursor, etc) for data analysis & management, and general ...

Work may include statistical analysis, simulation, computer modeling, linear programming, data mining, and visualization of large or complex data sets. * Provide business-focused advice and expertise ...

Develop mathematical optimization models using linear programming and integer linear programming methods * Develop analytical models to support decision-makers * Develop analytical algorithms to ...

Skills in Statistical analysis, linear programming, SQL, Power BI. * Skills in DOE (Design of Experiments), and process assessment and improvement. To Apply : Send resume to Alamance Foods Inc. at ...

At Linear, we're building the product development system for teams and agents. AI is fundamentally ... Product, Engineering, and GTM. We own our data pipelines, warehouse, dashboards, analysis, and ...

Job Overview: The Commercial Analytics group is looking for a Data Scientist to join our team ... Linear & Non-Linear Programming * Network Flow Models * Dynamic Programming * Simulation

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Linear Programming Analyst information

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How much do linear programming analyst jobs pay per hour?

As of Sep 10, 2026, the average hourly pay for linear programming analyst in the United States is $46.48, according to ZipRecruiter salary data. Most workers in this role earn between $36.06 and $56.49 per hour, depending on experience, location, and employer.

What does a linear programming analyst do?

A Linear Programming Analyst specializes in using mathematical models to optimize processes and decision-making in various industries. They formulate problems as linear equations and inequalities, then use computational techniques to find the best possible solutions within given constraints. Their work often helps organizations minimize costs, maximize profits, or efficiently allocate resources. These analysts collaborate with management and technical teams to interpret data and implement solutions. They play a critical role in industries like logistics, manufacturing, finance, and operations research.

What are the key skills and qualifications needed to thrive as a linear programming analyst?

To thrive as a Linear Programming Analyst, you need a solid background in mathematics, operations research, and data analysis, typically supported by a degree in mathematics, engineering, or a related field. Proficiency in optimization software such as CPLEX or Gurobi, programming languages like Python or MATLAB, and familiarity with data visualization tools are commonly required. Strong analytical thinking, problem-solving abilities, and effective communication skills help you interpret results and present complex solutions to stakeholders. These competencies are essential for developing efficient models that drive informed decision-making and optimize organizational performance.

What are some common challenges faced by linear programming analysts when implementing optimization solutions in real-world business settings?

Linear Programming Analysts often encounter challenges such as dealing with incomplete or inconsistent data, managing complex constraints that may not be easily translated into mathematical models, and ensuring stakeholder buy-in for recommended solutions. Additionally, real-world problems can change over time, requiring analysts to frequently update and adapt their models. Effective communication is also crucial, as analysts must explain technical results to non-technical team members and collaborate with various departments to ensure successful implementation.

What is the difference between Linear Programming Analyst vs Operations Research Analyst?

AspectLinear Programming AnalystOperations Research Analyst
Required CredentialsBachelor's degree in mathematics, statistics, or related field; certifications like CAP or PMPBachelor's or master's in operations research, mathematics, or engineering; similar certifications
Work EnvironmentCorporate offices, consulting firms, government agenciesSimilar settings, often in consulting, government, or large corporations
Industry UsageSupply chain, logistics, manufacturing, financeLogistics, transportation, healthcare, manufacturing
Job FocusDeveloping and applying linear programming models to optimize processesAnalyzing complex systems to improve decision-making using various analytical methods

Both roles involve analytical skills and quantitative modeling, but Linear Programming Analysts primarily focus on linear models for optimization, while Operations Research Analysts use a broader range of techniques to solve complex problems across industries.

More about Linear Programming Analyst jobs

What states have the most Linear Programming Analyst jobs?

States with the most job openings for Linear Programming Analyst jobs include:

What are popular job titles related to Linear Programming Analyst jobs?

For Linear Programming Analyst jobs, the most frequently searched job titles are:

Infographic showing various Linear Programming Analyst job openings in the United States as of September 2026, with employment types broken down into 2% Internship, 82% Full Time, 12% Part Time, 3% Contract, and 1% Nights. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $96,677 per year, or $46.5 per hour.

Operations Research / Systems Analyst (ORSA) - Optimization & Mathematical Programming

Hanover, MD • On-site

SMX
IT Services • 1 - 5K employees

$98K - $115K/yr

Full-time

Medical, Retirement, PTO

Re-posted 26 days ago


Job description

The Operations Research (OR) Analyst - Optimization & Mathematical Programming Focus provides advanced optimization, resource allocation, and prescriptive analytics across a Federal Agency's personnel vetting, industrial security, and counterintelligence operations. This position formulates and solves complex mathematical programming problems that enable the Federal Agency to optimize resource deployment, prioritize competing requirements, and transition from reactive decision-making toward mathematically grounded, optimal resource allocation strategies.
Essential Duties and Responsibilities
Mathematical Optimization & Resource Allocation
  • Formulate real-world resource allocation problems as mathematical optimization models (linear programming, integer programming, mixed-integer programming)
  • Develop and implement optimization algorithms for complex assignment problems including adjudicator workload distribution, facility inspection scheduling, and investigator allocation
  • Apply constraint programming and heuristic methods to solve large-scale, computationally challenging optimization problems
  • Build decision support tools that enable operational leaders to explore tradeoffs and make resource deployment decisions with mathematical rigor

Strategic Analysis & Decision Support
  • Conduct cost-benefit analyses and apply mathematical programming techniques to optimize the distribution of personnel, budgetary, and operational resources across competing requirements
  • Apply risk-based optimization to prioritize facility assessments, case assignments, and inspection schedules based on threat levels and resource constraints
  • Perform trade-space analysis and sensitivity studies to understand how optimal solutions change under different assumptions, constraints, or objectives
  • Develop multi-objective optimization approaches that balance competing goals (speed, quality, cost, risk mitigation)

Model Development & Implementation
  • Utilize optimization solvers (Gurobi, CPLEX, or open-source alternatives like Pyomo, PuLP, OR-Tools) to implement and solve mathematical models
  • Validate optimization model outputs against historical operational data and subject matter expert judgment
  • Develop prescriptive analytics that recommend specific actions based on optimization results
  • Create scenario planning tools that allow decision-makers to explore "what-if" questions regarding resource allocation strategies

Collaboration & Communication
  • Work closely with modeling/simulation specialists to incorporate predictive analytics into optimization formulations
  • Partner with data engineering specialists to obtain empirically-grounded parameters, constraints, and objective function coefficients
  • Translate mathematical optimization results into clear, actionable recommendations for non-technical decision-makers
  • Present optimization approaches, tradeoff analyses, and recommendations to senior leadership
  • Participate in cross-functional team activities to maintain technical standards and share knowledge

Required Skills & Experience
  • 8+ years of progressive, hands-on operations research experience, including demonstrated application of mathematical optimization, resource allocation modeling, and prescriptive analytics to real-world operational problems
  • 3-5 years of that experience supporting DoD or Intelligence Community mission areas such as personnel vetting, industrial security (NISP), counterintelligence, or insider threat
  • Expert-level proficiency in mathematical optimization including linear programming, integer programming, and mixed-integer programming
  • Hands-on experience with optimization solvers (Gurobi, CPLEX, FICO Xpress, or open-source alternatives such as Pyomo, PuLP, OR-Tools, COIN-OR)
  • Demonstrated ability to formulate real-world problems as mathematical programs, including objective function design and constraint identification
  • Proven proficiency in an analytical programming language (Python or R), with emphasis on optimization modeling libraries
  • Experience with constraint programming and heuristic solution methods for large-scale or computationally difficult problems
  • Strong foundation in algorithm design, computational complexity, and solution methods
  • Ability to validate optimization models using operational data and communicate results to non-technical stakeholders
  • Experience working in secure (classified) government environments
  • Secret clearance required (active or ability to obtain)

Desired Skills & Experience
  • Advanced degree in Operations Research, Applied Mathematics, Industrial Engineering, Management Science, or a related quantitative discipline
  • Familiarity with NISP, clearance adjudication processes, and/or insider threat/counterintelligence analytic frameworks
  • Experience with nonlinear optimization and stochastic optimization techniques
  • Knowledge of multi-objective optimization and Pareto analysis
  • Network optimization and graph algorithms (shortest path, max flow, matching problems)
  • Experience with scheduling and routing problems (job shop scheduling, vehicle routing)
  • Familiarity with game theory and decision analysis under uncertainty
  • Knowledge of operations research software (AMPL, GAMS)
  • Data visualization tools (Tableau, Power BI) for communicating optimization results
  • SQL and database querying skills to support model parameterization
  • Knowledge of queueing theory and simulation to better integrate with modeling specialists
  • Experience with statistical modeling and risk analysis to inform optimization formulations

The SMX salary determination process takes into account a number of factors, including but not limited to, geographic location, Federal Government contract labor categories, relevant prior work experience, specific skills, education and certifications. At SMX, one of our Core Values is to Invest in Our People so we offer a competitive mix of compensation, learning & development opportunities, and benefits. Some key components of our robust benefits include health insurance, paid leave, and retirement.
The proposed salary for this position is:
$123,000-$206,000 USD
At SMX®, we are a team of technical and domain experts dedicated to enabling your mission. From priority national security initiatives for the DoD to highly assured and compliant solutions for healthcare, we understand that digital transformation is key to your future success.
We share your vision for the future and strive to accelerate your impact on the world. We bring both cutting edge technology and an expansive view of what's possible to every engagement. Our delivery model and unique approaches harness our deep technical and domain knowledge, providing forward-looking insights and practical solutions to power secure mission acceleration.
SMX is an Equal Opportunity employer including disabilities and veterans.
Selected applicant may be subject to a background investigation and/or education verification.
SMX does not sponsor a new applicant for employment authorization or immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer).

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About SMX

Sourced by ZipRecruiter

Our tradition of delivering innovative, technical solutions dates back to 1995, however, you may know us better by one of our legacy company names: Trident Technologies, Smartronix, Datastrong or C2S Consulting Group. With the support of OceanSound Partners, our private equity investment sponsor, we began operating as one business starting in 2019 and became SMX in 2021. We operate in close proximity to our clients around the globe and have core locations in Alabama, California, DC Metro, Florida, Hawaii, Maryland, and Massachusetts. Today, as SMX, we are one team and together empower government and commercial enterprises to become more effective, innovative, and resilient, no matter what challenges they face.

Industry

It services

Company size

1,001 - 5,000 Employees

Headquarters location

Hollywood, MD, US