I am passionate about solving problems that impact people's lives by coupling my business intelligence experiences with strong research and data science skills. I have substantial experience extracting, cleaning, transforming, and analyzing large data sets to build predictive models and deliver actionable insights. Furthermore, I am well-versed in creating clear and intuitive visualizations to effectively communicate ideas and results.
Data Science Development Manager, Oracle
May 2017 to Present
Principal Data Scientist, Utility Services, Oracle
May 2014 to Present
Overview: Advance product features through R&D, and deliver custom end-to-end analytic solutions for utility clients Combine statistical and machine learning approaches to improve foundational analytics -- Segmented seasonal consumption behavior by applying signal processing techniques and clustering algorithms -- Clustered meters based on voltage signatures to distinguish power phases, resulting in a 98% accuracy score Detected orphaned meters using classification algorithms, resulting in a 75% hit rate, and found an additional 20% new mis-mapped meters–patent accepted by the US Patent and Trademark Office Predict transformer failures by iterating through several rounds of feature engineering, and applied and tuned several classification models, ultimately increasing the hit rate from 5% to 30% Develop data ingestion processes and testing frameworks for input into core product algorithms and UI configurations for different utility functions Collaborated with development and product teams to improve algorithm performance, UI design, and expand product features based on story-boarding customer roles and use-cases Mentored junior data science team members through the full lifecycle of ambiguous analytic projects, thereby broadening their statistical skillsets and refining their problem-solving abilities