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Power Trade Analytics Lead
hace 4 semanas
ENGIE Mexico, Energy at the service of the country
We are committed to providing energy and better living conditions to the Mexicans that we proudly serve.
We act to accelerate the energy transition towards a carbon-neutral economy, by reducing energy consumption and developing more environmentally friendly solutions.
Our purpose brings to the whole society, represented by our employees, customers and shareholders, reconciling ENGIE's business model with a positive impact on planet and people.
Our key figures in Mexico:
• 25 years presence in Mexico
• 2.5 million Mexicans supplied with one of our energy solutions
• 20,000 jobs (direct and indirect)
• 31% of women in leadership positions
• 3.42 USD Million of investment in Mexico
• 1st Private Buyer of Natural Gas in Mexico
• 2nd Natural Gas Distributor in Mexico
• 10 natural gas distribution areas
• +650,000 customers in Natural Gas Distribution in residential segment
• 4 Natural Gas Transport Companies with +1,300 km of gas pipelines
• 2 Power Generation Plants with 280 MW based on natural gas
• 1 GW of 100% clean energy generated by 2 wind and 6 solar plants.
Power Trade Analytics Lead
Purpose of the Position:
Design quantitative models to support risk management strategy, pricing and product design, through improved understanding of daily market conditions and it’s impact on mid and long term pricing curve, and correlations across Mexico’s interconnected system
Responsabilities and Job Functions:
Advanced mathematical model development:Propose and develop models that represent power market conditions with high precision.
Design mathematical / data solutions to support trading, pricing and asset optimization activities for GEMS and other GBU.
Strategic cross-team collaboration for effective solution design:Contribute to strategic business development activities in GEMS (e.g. Proyecto Enlace, Aligne, Risk Management Services, among others) building bridges between commercial work and market analysis activities.
Work closely with other areas of business to ensure models follow a (internal) client-centric approach.
Provide support as subject matter expert to help improve existing in-house models:Build a strong network and collaborate with GEMS’ regional and global network of experts (GMA - Global Market Analysis) network of experts.
Digital & Innovation:Contribute towards the development of a strong digital culture, ensuring models are scaled to operate in existing GEMS’ digital environment. For this, the selected candidate will collaborate closely with GEMS’ D&I team.
Executive communication and storytelling:Contribute to internal debate on best possible modeling approach within an uncertain environment and with limited market data.
Support model adoption through easy to grasp presentations.
Market analysis and reporting:Contribute to broader Market Intelligence efforts (i.e. market conditions monitoring, reporting, Power Outook quality assurance) when required.
Customer Satisfaction:Ensure all models serve a value creation purpose and fit within GEMS business strategy and internal costumer needs.
Ocupational Profile:
Required educational background: Bachelor’s Degree (essential) (Mathematics, Engineering, Digital Science) or Higher Degree (ideal) (Energy Markets, Digital Science, Engineering, etc.).
Expirience: At least 3 years working in mathematical modeling and experience in:
Mexico Energy Industry Network Digital Science and product development Data based business intelligence Market analysisTechnical Skills:
Essential: Applied mathematics skills, proven experience in design and implementation of advanced analytics models (e.g. neural analysis, Montecarlo simulations, genetic, advanced Office skills (Excel, PowerBI) Preferred: Programming skills, Energy, Commodities, Trading, Power Markets, EconomicsAt ENGIE we pursue your feeling free to be what you are. We are commited to equality for opportunities and we value the diversity in each person. When we choose our talent, we focus on the skills and the career path. We do not discriminate based on person's race, disability, religion, gender, sexual orientation, ethnicity, creed, age, or civil status.
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