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Operations Research Phd Jobs in Texas (NOW HIRING)

Amazon

Applied Scientist, Last Mile Science

Austin, TX · On-site

... PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field - Experience in patents or publications at ...

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Operations Research Phd information

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$35.9K

$87.4K

$140.7K

How much do operations research phd jobs pay per year?

As of Sep 2, 2026, the average yearly pay for operations research phd in Texas is $87,393.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,000.00 and $107,600.00 per year, depending on experience, location, and employer.

What is an operations research PhD?

Operations Research PhDs are experts who have completed a doctoral program focused on advanced analytical methods to help make better decisions and solve complex problems. Their studies involve mathematics, statistics, computer science, and engineering principles to develop models and algorithms used in industries such as logistics, finance, healthcare, and manufacturing. With a PhD, they often pursue careers in academia, industry research, or consulting, applying their expertise to optimize systems and processes.

What are the key skills and qualifications needed to thrive as an operations research PhD?

To thrive as an Operations Research PhD, you need advanced analytical skills, a strong foundation in mathematics and statistics, and a doctoral degree in operations research or a related quantitative field. Expertise with optimization software (like CPLEX or Gurobi), programming languages (such as Python, R, or MATLAB), and familiarity with data analysis tools are typically required. Strong problem-solving abilities, effective communication, and the ability to work collaboratively distinguish top performers in this role. These skills enable professionals to develop data-driven solutions to complex business problems and communicate insights to stakeholders, driving organizational efficiency and innovation.

What are some common challenges faced by operations research PhDs when transitioning from academia to industry roles?

One common challenge for Operations Research PhDs moving into industry is adapting to the faster-paced environment where solutions often need to be practical and implemented quickly, rather than purely theoretically optimal. Additionally, communicating complex analytical methods to non-technical stakeholders and working within cross-functional teams requires strong collaboration and interpersonal skills. Industry roles may also demand proficiency with industry-specific tools and the ability to manage multiple projects with shifting priorities. Embracing these challenges can accelerate professional growth and lead to rewarding career advancement.

What are popular job titles related to Operations Research Phd jobs in Texas?

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What job categories do people searching Operations Research Phd jobs in Texas look for?

The top searched job categories for Operations Research Phd jobs in Texas are:

What cities in Texas are hiring for Operations Research Phd jobs?

Cities in Texas with the most Operations Research Phd job openings:

Operations Research Phd jobs near you
Infographic showing various Operations Research Phd job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 10% Part Time, 1% Temporary, 2% Contract, and 1% Nights. Highlights an 93% Physical, 3% Hybrid, and 4% Remote job distribution, with an average salary of $87,393 per year, or $42 per hour.

Senior Data Scientist - Operation Research

Tiger Analytics Inc.

Dallas, TX • On-site, Remote

Full-time

Re-posted 9 days ago

Job description

Tiger Analytics is pioneering what AI and analytics can do to solve some of the toughest problems faced by organizations globally. We develop bespoke solutions powered by data and technology for several Fortune 100 companies. We have offices in multiple cities across the US, UK, India, and Singapore, and a substantial remote global workforce.
We are also market leaders in AI and analytics consulting in the CPG & retail industry with over 40% of our revenues coming from the sector. This is our fastest-growing sector, and we are beefing up our talent in the space.
We are looking for a Senior Data Scientist with a good blend of data analytics background, practical experience in Operation research strategies and Pricing Analytics within supply chains, and strong coding capabilities to add to our team.
Key Responsibilities:
  • Responsible for refactoring the Optimization algorithm written in Python using Object Oriented Programming
  • Work on the latest applications of data science to solve business problems in the Supply chain and optimization space of Retail and/or CPG.
  • Utilize advanced statistical techniques and data science algorithms to analyze large datasets and derive actionable insights related to Pricing Optimization.
  • Develop and implement predictive models and optimization algorithms to improve inventory management, reduce stockouts, and optimize resource allocation across the supply chain.
  • Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions.
  • Design and execute experiments to evaluate the effectiveness of different replenishment strategies and allocation policies.
  • Monitor and analyze key performance indicators (KPIs) related to replenishment and supply chain allocation, and provide recommendations for continuous improvement.
  • Stay abreast of industry trends and best practices in data science, replenishment optimization, and supply chain management, and leverage this knowledge to drive innovation within the organization.
  • Collaborate, coach, and learn with a growing team of experienced Data Scientists.

Requirements
  • Proven experience 10+ years working as a Data Scientist, with a focus on supply chain optimization and inventory allocation.
  • MS or PhD in Computer Science, Operations Research, Applied Mathematics, Machine Learning, or a related field.
  • Experience with using mathematical programming solvers such as Gurobi, Xpress MP, CPLEX, or Google OR Tools in applications.
  • Solid understanding of statistical methods, optimization techniques, and predictive modelling concepts.
  • Strong proficiency in programming languages such as Python, Pyspark and SQL, and experience working with data analysis and machine learning libraries.
  • Ability to apply various analytical models to business use cases
  • Exceptional communication and collaboration skills to understand business partner needs and deliver solutions and explain to business stakeholders.

Benefits
This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.

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