THE TEAM YOU WILL BE JOINING:
- High-growth company, boasting substantial revenue of over $500 million
- Innovative and forward-thinking organization that is leading the way in its industry.
- Benefit from the stability and success of a company with strong revenue growth and a solid market presence.
- Contribute to a sizable workforce of industry experts and talented professionals, fostering a dynamic and collaborative environment.
WHAT THEY OFFER YOU: - State-of-the-art new office space that offers a collaborative work environment
- Opportunity to make a huge impact on building new culture, and evolving the company into a "future state"
- Offers a competitive compensation package, a culture that values teamwork, respect, accountability, and flexibility
WHY THIS ROLE IS IMPORTANT: - Develop and deploy machine learning/deep learning models to predict energy production, and enhance asset performance.
- Analyze large datasets from solar, wind, battery storage, and other renewable energy sources to identify trends and actionable insights.
- Collaborate with engineers, analysts, and business stakeholders to integrate data science solutions into operations and strategy.
- Implement predictive maintenance models to reduce downtime and improve asset reliability.
- Utilize geospatial and weather data for energy forecasting and site selection.
- Design and optimize algorithms for energy trading, load balancing, and grid stability.
- Build and maintain scalable data pipelines to process real-time and historical energy data.
- Communicate findings through data visualizations, dashboards, and reports for executive decision-making.
- Stay up-to-date with advancements in AI, machine learning, and energy analytics to drive innovation.
THE BACKGROUND THAT FITS: - 5+ years of hands-on experience as a Data Scientist in an industrial setting.
- Strong programming skills in Python, SQL.
- Experience with machine learning frameworks (TensorFlow, scikit-learn, PyTorch, Keras) and data visualization tools (Tableau, Power BI, Matplotlib).
- Expertise in working with time-series data and statistical modeling.
- Familiarity with cloud platforms (AWS, Azure, Google Cloud) and big data technologies (Spark, Hadoop).
- Knowledge of renewable energy systems, grid optimization, and forecasting models.
- Strong problem-solving and communication skills
- Bachelor s or Master s degree in Data Science, Computer Science, Engineering, Statistics, or a related field.