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Data Science Renewable Energy Jobs in Texas (NOW HIRING)

Through open, data-driven applications, the platform enables renewable energy organizations to ... science libraries (pandas, NumPy, scikit-learn, TensorFlow / PyTorch, etc.) Strong grounding in ...

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Data Science Renewable Energy information

See Texas salary details

$19.8K

$81.4K

$169.7K

How much do data science renewable energy jobs pay per year?

As of Sep 4, 2026, the average yearly pay for data science renewable energy in Texas is $81,362.00, according to ZipRecruiter salary data. Most workers in this role earn between $38,695.00 and $115,645.00 per year, depending on experience, location, and employer.

What is a data science renewable energy?

A Data Science Renewable Energy job involves using data analytics, machine learning, and statistical techniques to optimize renewable energy production, grid management, and resource forecasting. Professionals in this field analyze large datasets from solar panels, wind turbines, and energy grids to improve efficiency, predict energy output, and reduce costs. They work with energy companies, utilities, and research institutions to develop models that enhance decision-making and sustainability. This role often requires expertise in programming, data visualization, and energy systems.

What types of projects do data science renewable energy professionals typically work on?

Data Science Renewable Energy professionals are usually involved in projects like optimizing energy production, forecasting demand and supply using weather and market data, and improving grid efficiency with predictive analytics. They often analyze large datasets from solar, wind, or other renewable sources to identify trends, inform decision-making, or reduce costs. Collaboration with engineers, project managers, and policy experts is common to design practical solutions for real-world energy challenges. This diverse range of projects offers opportunities for both technical innovation and direct impact on sustainability goals.

What are the key skills and qualifications needed to thrive in data science renewable energy, and why are they important?

To excel in a Data Science Renewable Energy role, you need a strong background in statistics, machine learning, and renewable energy systems, often backed by a relevant degree in data science, engineering, or a related field. Proficiency with data analytics tools such as Python, R, SQL, and platforms like TensorFlow, as well as experience with energy industry software, are highly valued, and certifications in data analytics or sustainability can be advantageous. Outstanding problem-solving skills, effective communication, and the ability to work collaboratively across multidisciplinary teams are essential soft skills. These abilities ensure accurate data-driven insights that optimize renewable energy operations, support sustainability goals, and drive innovation in a rapidly evolving sector.

What are the most commonly searched types of Data Science Renewable Energy jobs in Texas?

The most popular types of Data Science Renewable Energy jobs in Texas are:

What are popular job titles related to Data Science Renewable Energy jobs in Texas?

For Data Science Renewable Energy jobs in Texas, the most frequently searched job titles are:

What cities in Texas are hiring for Data Science Renewable Energy jobs?

Cities in Texas with the most Data Science Renewable Energy job openings:

Infographic showing various Data Science Renewable Energy job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $81,362 per year, or $39.1 per hour.

Data Scientist - Hedging & Risk Management (Renewables)

ENGIE Group

Houston, TX โ€ข On-site

$117 - $180/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 12 days ago


Key responsibilities

  • Design and implement scalable digital solutions to automate manual processes and improve operational efficiency in risk management and hedging activities

  • Develop predictive models, analytical frameworks, and risk metrics to evaluate market, operational, and portfolio performance and support decision-making

  • Automate financial, portfolio, and risk reporting processes and create dashboards and visualizations to communicate insights to stakeholders


Job description

ENGIE North America is seeking a highly analytical and technically skilled Data Scientist to join the Hedging & Risk Management team supporting our renewable energy portfolio. In this role, you will apply advanced analytics, data science, and technology to transform complex markets, portfolio, and risk data into actionable insights that strengthen decision-making and support the financial performance of our renewable assets.

You will combine expertise in data science, software development, financial modeling, and cloud-based analytics platforms to develop scalable analytical tools, automate processes, enhance risk and exposure mapping, and improve the quality and speed of commercial insights. Working closely with Hedging & Risk Management and cross-functional partners, you will play a key role in advancing the team's digital capabilities and enabling more informed, data-driven risk management decisions.

What You Will Do Digital Transformation & Process Optimization
  • Design and implement scalable digital solutions that replace manual processes, improve operational efficiency, and strengthen decision-making across Hedging & Risk Management
  • Maintain and enhance digital platforms supporting renewable energy and battery energy storage system (BESS) activities
  • Identify and implement opportunities to automate data collection, validation, workflow, and reporting processes
  • Drive continuous improvement initiatives across risk management, hedging, and commercial operations
Advanced Analytics & Model Development
  • Develop predictive models, optimization algorithms, and analytical frameworks that support portfolio, commercial, and risk management objectives
  • Apply statistical modeling, machine learning, and quantitative techniques to evaluate market, operational, and portfolio performance
  • Build scalable analytical tools for forecasting, scenario analysis, sensitivity analysis, and performance benchmarking
  • Translate complex data and model outputs into actionable insights for business stakeholders
  • Design methodologies to identify, quantify, monitor, and visualize market, operational, and financial risk exposures across renewable and battery storage portfolios
  • Develop risk metrics, analytical frameworks, and dashboards that improve visibility into portfolio exposures and performance
  • Perform stress testing and sensitivity analysis to evaluate portfolio response to changing market and operational conditions
  • Enhance risk reporting capabilities through improved analytics, automation, and data visualization
  • Partner with Group Risk, short-term trading, and commercial teams to evaluate hedging strategies, market exposures, and portfolio performance
  • Deliver quantitative analysis that supports price risk management, portfolio optimization, and strategic decision-making
  • Develop tools and methodologies to assess hedge effectiveness, market exposure, and the financial impacts of alternative hedging strategies
  • Provide analytical support for evolving renewable and BESS risk management strategies
Business Intelligence & Data Visualization
  • Automate recurring financial, portfolio, and risk reporting using modern data platforms and business intelligence tools
  • Develop dashboards and self-service analytics solutions using Power BI and other visualization platforms
  • Transform complex datasets into intuitive visualizations that enable stakeholders to quickly understand trends, exposures, and performance
  • Maintain data quality, integrity, governance, and traceability across analytical models, tools, and reporting solutions
What Youโ€™ll Bring Education & Technical Expertise
  • Bachelorโ€™s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Economics, Finance, or a related quantitative discipline; a masterโ€™s degree in a quantitative discipline may complement relevant experience but is not required
  • Minimum seven (7) years of relevant experience in data science, advanced analytics, quantitative or predictive modeling, market risk analysis, hedging, or related analytical roles
  • Advanced proficiency in Python with experience developing reliable, scalable analytical solutions
  • Proficiency in SQL and experience working with relational databases, complex datasets, and cloud-based data and analytics platforms such as Databricks, Microsoft Fabric, Azure, Snowflake, or comparable technologies
  • Experience applying statistical modeling, machine learning, optimization, forecasting, or other quantitative techniques to solve business problems
  • Proficiency with business intelligence and data visualization tools such as Power BI, Tableau, or equivalent platforms
Analytics, Communication & Delivery
  • Demonstrated analytical and problem-solving capabilities with the ability to translate complex data, models, and findings into meaningful business insights
  • Ability to communicate technical concepts and recommendations clearly to technical and non-technical stakeholders
  • Demonstrated ability to manage analytical initiatives from development through implementation and continuous improvement while collaborating effectively across cross-functional teams
  • Commitment to data quality, accuracy, governance, and analytical integrity
Experience in one or more of the following will help you succeed in this role:
  • Experience with energy markets, renewable energy, battery storage, power generation, commodity trading, quantitative finance, or market risk management
  • Knowledge pf North American wholesale power markets such as ERCOT, CAISO, PJM, MISO, or SPP
  • Knowledge of hedging instruments, financial derivatives, portfolio analytics, or market risk management concepts
  • Experience developing forecasting, optimization, portfolio analytics, or risk management solutions
  • Familiarity with software engineering practices including version control, testing, CI/CD, or cloud deployment
  • Experience ap plying artificial intelligence, including generative AI, to analytics, forecasting, automation, or decision-support processes
  • This role is eligible for our hybrid in-office work policy
  • Must be available to travel domestically up to 10% of the time with the need for some overnight trips
  • Must be willing and able to comply with all ENGIE ethics and safety policies
Compensation

Salary Range: $117,300 โ€“ $179,860 USD annually

This represents the average expected pay range for a qualified candidate. ENGIE complies with all federal, state, and local minimum wage laws. Actual salary offered may vary depending on geography, experience, education, internal pay alignment, or other bona fide factors.

In addition to base pay, this position is eligible for a competitive bonus / incentive plan.

Your Talent Acquisition Partner can share more specific information regarding the benefits or the salary for the position based on the work location.

At ENGIE, we take your well-being seriously. Our comprehensive benefits package includes options for medical, dental, vision, life insurance, employer-paid short-term and long-term disability insurance, ESPP, generous paid time off including wellness days, holidays and leave programs. We also help you plan for retirement by offering a 401(k) Retirement Savings Plan with a company match. But that's not all โ€“ we're dedicated to the health and happiness of your entire family, offering supplemental benefits for full time employees that enhance emotional and physical well-being through all stages of life from family forming to caregiver benefits. Explore our benefits package to see how we can support you. Learn more .

Why ENGIE?

ENGIE North America isnโ€™t just participating in the Zero-Carbon Transition, weโ€™re leading it! Join us as we develop energy that is renewable, efficient, and accessible to everyone.

At ENGIE, every talent has a role to play in the adventure of the century. Make a difference and enjoy a fulfilling professional experience. Take on exciting challenges and build a career path that reflects who you are.

Join us and be part of the adventure!

ENGIE is proud to be an equal opportunity workplace, and we are firmly committed to creating an inclusive workplace for all employees. We are committed to providing employees with a work environment free of discrimination and harassment. All qualified applicants will receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, disability, veteran status, or other legally protected status.

If you need assistance with this application or a reasonable accommodation due to a disability, you may contact us at ENGIENA-ENGIEHR@engie.com. This email address is reserved for individuals with disabilities in need of assistance and is not a means of inquiry regarding positions or application status.

We are unable to sponsor or take over sponsorship of an employment visa for this role at any time.

The safety of our employees is our number one priority. All employees at ENGIE have both a duty and the authority to STOP WORK if unsafe acts are observed.

Business Unit: GBU Renewables & Flexible Power

Company Name: ENGIE North America

Minimum Base Salary:

Maximum Base Salary:

Pay Basis:

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