Intern, Data Scientist - Hedging and Risk Management

What You Can Expect

ENGIE North America is seeking a highly skilled and motivated Data Scientist, Intern to join our Hedging and Risk Management team. This role is pivotal in driving data-driven decision-making and accelerating digital transformation across our financial and risk operations.

 

As an intern, you will leverage advanced analytics, coding expertise, and modern data platforms to build scalable tools that enhance performance, support strategic hedging, and streamline reporting processes. You’ll collaborate with cross-functional teams to translate complex data into actionable insights that drive business value.

 

This internship offers a dynamic and fast-paced environment, requiring a high level of flexibility and the ability to manage multiple projects simultaneously. You should be comfortable pivoting quickly as priorities shift and demonstrate strong organizational skills, adaptability, and a proactive mindset to thrive in this role.

 

What You’ll Do

As a Data Scientist, Intern on our Hedging and Risk Management team, you will be responsible for:

• Process Digitalization: Design and implement digital solutions to replace manual workflows and improve operational efficiency
• Advanced Analytics & Tool Development: Create scalable tools and algorithms for predictive modeling, scenario analysis, and optimization
• Performance Optimization: Develop models and dashboards to monitor and improve financial and operational performance
• Financial Reporting Automation: Automate and enhance reporting processes using data pipelines and visualization tools
• Risk Mapping & Visualization: Build analytical frameworks to identify, quantify, and visualize risk exposures across portfolio
• Support Strategic Hedging: Provide data-driven insights to inform and evaluate hedging decisions and strategies

 

 

What You’ll Bring

To succeed in this role, you’ll bring a blend of technical experience, analytical thinking, and financial acumen. 

• Open to juniors, seniors, or graduate students currently enrolled in a university/college degree program related to computer science, information technology, sciences, or other relevant technical fields

• Advanced Coding Skills: Proficiency in Python, with experience writing clean, modular, and scalable code
• Experience with Modern Data Platforms: Hands-on experience with Databricks, Microsoft Fabric, or similar cloud-based data environments
• Analytical Expertise: Background in statistics, machine learning, and data modeling
• Data Visualization Proficiency: Familiarity with tools such as Power BI to create intuitive dashboards and visual reports
• Financial & Risk Knowledge: Understanding of hedging instruments and financial derivatives, with the ability to apply data science techniques to risk management strategies

 

Additional Details

• The internship term will run from January 2026 to August 2026. Please note that this role follows ENGIE’s hybrid in-office work policy, requiring regular on-site presence—it is not eligible for remote work
• Interns must be enrolled in good standing at the commencement of the intern semester
• Must be willing and able to comply with all ENGIE ethics and safety policies

 

Compensation

Hourly Range: $25.50 - $33.50 USD hourly

 

This represents the average expected pay range for a qualified candidate.

 

Actual offered salary may depend on geography, experience, industry knowledge, education, internal pay alignment, or other bona fide factors.

 

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. 

 

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

 

Why ENGIE?

ENGIE North America isn’t just participating in the Zero-Carbon Transition, we’re leading it!  Join us as we develop energy that is renewable, efficient, and accessible to everyone.  

 

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