Sandra Villamar

About Sandra Villamar

Data scientist and machine learning engineer with a strong mathematical foundation. I strive to utilize my technical skills towards creating a sustainable future.Skills:Python | R | MATLAB | SQL | GraphQL | GitHub | Databricks | Production Deployments | Solar Energy | Climate | Numerical Analysis & Optimization | Probability & Statistics | Generative & Discriminative Models | Statistical Learning | Data Analysis & Visualization | Dimensionality Reduction | Clustering Analysis | Optimization | SVM | Neural Networks | Boosting | Time Series Forecasting | Web Search | Similarity Query & Hashing | Data Streaming | Recommender Systems | English, German, SpanishI also value a work/life balance and strongly believe that happiness is the key to success. In my free time, I enjoy dancing, kickboxing, snowboarding, and searching for the best coffee in town!

Experience

1. Solar Data Scientist

   Power Factors

   Aug 2023 — Present · San Diego, CA, US

   Improved the inverter underperformance LightGBM classifier by 35% by establishing data collection requirements, conducting extensive feature engineering and selection, and training via Databricks with custom train-test split, class weights, and hyperparameter search space.• Deployed the inverter underperformance classifier on a completely new tech stack which made it possible to consume, calculate, and write everything needed within an acceptable resource limit.• Developed an inverter twin model, a dynamic baseline capturing unimpaired inverter performance with robust regression, to identify data quality issues, any seasonal or long-term effects such as module degradation, and provide reasonable expected production coefficients.• Generated our product\'s first ever insights that tie our features\' findings to actionable items, increasing customer awareness and productivity.• Created method to identify irradiance sensors that are miscalibrated, stalled, or shaded.• Invited to speak at two conferences about the intersection of AI and Energy.

Education

• UC San Diego Jacobs School of Engineering

  M.S. in Machine Learning and Data Science

• UC San Diego

  B.S. in Applied Mathematics, Minor in Economics

  2017 — 2020