Tasks

• Develop a predictive model on the wind energy production forecast
• Analyze historical data for accuracy
• Implement and test the model

Challenges

Accurately forecast wind energy production based on historical data.

Solutions

• Developed a predictive model for wind energy production
• Utilized historical data for training and testing the model
• Implemented machine learning techniques to enhance forecast accuracy

Outcomes

• Model Forecast – mean Absolute Percentage Error was <10

Technologies Used

Tasks

Challenges

Solutions

• Conducted a detailed analysis of Reface’s technical needs and long-term R&D objectives.
• Implemented a targeted recruitment strategy leveraging industry networks and AI-specific talent pools.
• Created a streamlined hiring process to evaluate both technical skills and cultural fit.

Outcomes

• Successfully hired Reface’s first core team of AI/ML engineers.
• Established a long-term partnership for ongoing AI talent acquisition.
• Supported Reface in maintaining its position as a globally recognized leader in AI-driven personalized content creation.