• Lead Vorto's development team across backend, web, mobile, data, IT, and security.• Product development and oversight for Vorto's new in-house trucking carrier, 5F.

• Lead Uplight's Connect Platform development division of 40+ individuals around the globe.  Responsible for our APIs, analytics, and data platform, as well as enterprise platform product.• Built an independent, empowered data & engineering management team. Individual pods maintain oversight of their costs, priorities, migration plans, and product roadmaps.• Key team member in closing flagship $85 million platform deal.  Involvement across sales, multilateral stakeholder discussions, technical scoping, SOW drafting, etc.• Tasked with evolving Uplight's data platform product into a larger multi-sided ecosystem play -- with an intent to grow the TAM for our business by creating a universal energy software platform• Supporting company wide migration from AWS to GCP by orchestrating a unified data lake, dev platform, and reporting systems across six acquired/merged companies•Support maintenance of product division and associated P&Ls

• Lead an 8-10 person cross-functional team of engineers, data science, and product. Team specialized in large scale asynchronous data engineering & warehousing efforts, machine learning, behavioral science & experimental design• Conceived and built team to deliver Tendril's energy analytics platform from scratch.  Acquired the first customers, grew the platform into a standalone product, and created new demand & revenue.  Product adopted by several of the Fortune 500.• Created systems to align a multitude of data sources ranging from transactional streams to bulk multi-TB data dumps into a living eventually consistent data lake and set of data marts• Guided efforts to collect, combine, and normalize a large array of disparate data sources into Tendril's single, live, cohesive view of the residential energy customer at a household-by-household level.• Performed deep M&A diligence that has directly resulted in $10s of millions of savings via adjusted bids after uncovering major flaws in management forecasts and user growth models

• Developed ETL and machine learning automation system adopted by the company as a whole. Featured Spark/AWS/Airflow, simple human config, and data catalog.  More full-featured than current AWS offerings, a year before Amazon's Glue release.• Guided migration of large Measurement & Validation system from legacy scripts to a production, monitored, cloud-based Python/Spark implementation• Developed solar panel detection pipeline that recorded & geocoded locations of installations by leveraging neural nets to analyze aerial imagery• Deployed high-throughput real-time solar lead scoring system that used demographics, home characteristics, and spatiotemporal installation data to predict propensity to install solar panels. Results featured by The Economist• Trained junior team on source control, CI/CD, monitoring, Python, and cloud software deployment

• Developed large scale image analysis pipelines for SM-TIRF applications that tracked and detected features across millions of scope images. Primarily C++ and Python.• Implemented novel algorithmic and machine-learning based feature detection algorithms geared towards computational performance and dim fluorophore signal.• Self-taught to design and perform SM-TIRF and protein biochemistry experiments.

• C development on brand new deployment of firmware for Intel SSDs. Primary focus on intermediary layer involving state capture and restoration from unexpected power interruption.