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Math Optimization Energy Phd Jobs (NOW HIRING)

Tenaska

Optimization Engineer

Irving, TX · On-site

... energy-related problems. * Support research and development of new optimization algorithms and ... Undergraduate degree in Physics, Mathematics, Engineering or related fields and graduate degree or ...

Tenaska, Inc.

Optimization Engineer

Irving, TX

... energy-related problems. * Support research and development of new optimization algorithms and ... Undergraduate degree in Physics, Mathematics, Engineering or related fields and graduate degree or ...

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How much do math optimization energy phd jobs pay per year?

As of Jun 6, 2026, the average yearly pay for math optimization energy phd in the United States is $58,837.00, according to ZipRecruiter salary data. Most workers in this role earn between $45,000.00 and $70,000.00 per year, depending on experience, location, and employer.

What is the difference between Math Optimization Energy Phd vs Data Scientist?

AspectMath Optimization Energy PhdData Scientist
Required CredentialsPhD in Mathematics, Optimization, or related fieldBachelor's or Master's in Data Science, Computer Science, or related field
Work EnvironmentResearch-focused, often in energy companies or R&D labsBusiness or tech companies, analytics teams
Industry UsageEnergy, utilities, research institutionsTech, finance, healthcare, retail

The Math Optimization Energy Phd specializes in advanced mathematical models and optimization techniques within the energy sector, often focusing on research and development. In contrast, Data Scientists analyze large datasets to extract insights and support decision-making across various industries. While both roles require strong analytical skills, the Phd role emphasizes theoretical and applied mathematics in energy contexts, whereas Data Scientists focus on data analysis and machine learning applications.

What is a Math Optimization Energy PhD?

A Math Optimization Energy PhD is an advanced doctoral degree focused on applying mathematical optimization techniques to solve complex problems in the energy sector. Students in this field develop mathematical models and algorithms to improve energy systems, such as electricity grids, renewable integration, and resource allocation. The program combines mathematics, computer science, and engineering concepts to address challenges like efficiency, sustainability, and cost in energy production and distribution. Graduates often pursue careers in academia, research institutions, or energy companies, working on innovative solutions for a sustainable energy future.

What types of interdisciplinary collaboration can I expect as a Math Optimization Energy PhD in the energy sector?

As a Math Optimization Energy PhD, you'll frequently work with multidisciplinary teams that include engineers, data scientists, policy analysts, and project managers. Your role typically involves developing mathematical models or algorithms to optimize energy systems, and you'll often need to translate complex results into actionable insights for colleagues with varying technical backgrounds. Collaboration may occur through regular meetings, joint research projects, and cross-functional workshops, making strong communication and teamwork skills essential. This environment offers opportunities to contribute directly to impactful projects, such as improving grid efficiency or advancing renewable energy integration.

What are the key skills and qualifications needed to thrive as a Math Optimization Energy PhD, and why are they important?

To thrive as a Math Optimization Energy PhD, you need advanced expertise in mathematical modeling, optimization techniques, and a deep understanding of energy systems, typically supported by a doctoral degree in a relevant field. Familiarity with optimization software (such as Gurobi or CPLEX), programming languages like Python or MATLAB, and experience with energy simulation tools are commonly required. Strong analytical thinking, problem-solving abilities, and effective communication skills set standout candidates apart. These skills are crucial for developing innovative solutions to complex energy challenges and effectively collaborating within multidisciplinary teams.
Research Engineer / Scientist - Optimization

Research Engineer / Scientist - Optimization

Percepta

Manhattan, NY • On-site

Full-time

Posted 27 days ago

Percepta rating

7.3

Company rating: 7.3 out of 10

Based on 23 frontline employees who took The Breakroom Quiz

14th of 71 rated call and contact centers

Job description

Job Summary:
Percepta is dedicated to transforming critical institutions through applied AI, focusing on industries such as healthcare, manufacturing, and energy. The Research Engineer/Scientist (Optimization) will work at the crossroads of AI research and practical application, driving advancements in decision-making by integrating machine learning with optimization research.
Responsibilities:
• Set and drive ambitious research programs that expand what’s achievable in data-driven decision-making.
• Invent new optimization-and-ML methods for high-impact problems such as planning, scheduling, routing, pricing, and inventory.
• Build high-fidelity simulators and rigorous benchmarks that mirror real-world constraints, uncertainty, and multi-objective trade-offs.
• Bridge research into practice by partnering with our engineers to rapidly prototype solutions and implement successful research ideas.
Qualifications:
Required:
• Hold a degree in Computer Science, Operations Research, Industrial Engineering, or Applied Mathematics (MS/PhD preferred) or have equivalent research/ industry experience.
• Have depth in operations or mathematical optimization (LP/MIP/MINLP, CP, stochastic/robust optimization, causal inference).
• Have experience in novel machine learning techniques for Operations Research.
• Are comfortable implementing and debugging large-scale optimization systems.
• Are motivated by impact in critical industries including healthcare, supply chains, energy, and finance.
• Have a proven track record of execution.
• Are an excellent communicator with both technical and non-technical stakeholders.
• Enjoy extreme ownership.
• Are passionate about AI’s transformative potential.
Company:
Percepta (a GC Transformation Company) combines applied AI engineering with frontier research to transform enterprises. Founded in 2025, the company is headquartered in New York, NY, US, , with a team of 11-50 employees. The company is currently Early Stage.

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