Team Lead, Data Scientist

Are you ready to be part of a company that's not just talking about the future, but actively shaping it? Join The AES Corporation (NYSE: AES), a Fortune 500 company that's leading the charge in the global energy revolution. With operations spanning 14 countries, AES is committed to shaping a future through innovation and collaboration. Our dedication to innovation has earned us recognition as one of the Top Ten Best Workplaces for Innovators by Fast Company in 2022. And with our certification as a Great Place to Work, you can be confident that you're joining a company that values its people just as much as its groundbreaking ideas.

AES is proudly ranked #1 globally in renewable energy sales to corporations, and with $12.7B in revenues in 2023, we have the resources and expertise to make a significant impact as we provide electricity to 25 million customers worldwide. As the world moves towards a net-zero future, AES is committed to meeting the Paris Agreement's goals by 2050. Our innovative solutions, such as 24/7 carbon-free energy for data centers, are setting the pace for rapid, global decarbonization.

If you're ready to be part of a company that's not just adapting to change, but driving it, AES is the place for you. We're not just building a cleaner, more sustainable future - we're powering it. Apply now and energize your career with a true leader in the global energy transformation.

At AES, our mission is to lead the energy sector into a sustainable future using renewable resources. As a global pioneer in Clean Energy, we are committed to innovating through data-driven solutions. By joining our Clean Energy Digital Analytics Team, you'll become part of a forward-thinking group dedicated to operational excellence and environmental sustainability. 

As the Team Lead for Machine Learning, you are essential to driving AES towards our goal of global leadership in renewable energy. Reporting to the Clean Energy Data and Analytics Manager, your role focuses on harnessing machine learning and artificial intelligence to drive significant business value, improve operational efficiency, and foster innovation in Clean Energy solutions. 

Duties and Responsibilities:  

• In alignment with the vision and framework of the Analytics Manager, support the development and lead a team of data scientists and machine learning specialists.

• Guide the team in creating high-impact AI/ML projects that are strategically aligned with AES Clean Energy's objectives and seamlessly integrated into the Clean Energy Digital Data & Analytics operating model. 

• Spearheading the development and implementation of AI/ML projects that deliver measurable business value, enhancing our operations and reinforcing our position in the clean energy sector, following our operating model by working hand by-hand with the rest of the areas of the Clean Energy Digital Analytics team. 

• Establishing and nurturing cross-functional collaborations, crafting machine learning models that bridge gaps between teams, thereby enabling and empowering them to amplify their results and optimize daily operations. 

• Designing and enforcing an AI/ML framework in collaboration with the other Clean Energy Data and Analytics areas, ensuring an end-to-end operating model with a primary focus on business value and innovation. 

• Overseeing the AI/ML initiatives within your team, ensuring alignment with business objectives and adherence to the best practices, frameworks, global digital standards, and operating models established by the leadership. 

• Serving as a trusted advisor to the Clean Energy’s Data & Analytics Manager and the Clean Energy’s Chief Digital Officer, as the main expert on AI/ML, constantly exploring, and experimenting with new avenues for applying machine learning to solve real-world energy challenges, while promoting a culture of continuous learning and adaptation. 

Qualifications and Experience: 

• Bachelor’s degree in computer science, Engineering, Data Science, Mathematics, or a related field; a Postgraduate degree in Data Science or Statistics is highly preferred. 

• 5 years minimum experience Data Science or Machine Learning 

• Extensive experience in machine learning or data science with proven expe