Personal details
Michael C.
Technical skills
About
Principal analytics, data, and AI engineer with 18+ years of experience building production financial systems, data pipelines, cloud infrastructure, computer-vision platforms, and applied AI products.
Combines deep Python, SQL, AWS, analytics, and systems architecture experience with strong financial and commercial judgment as a CFA charterholder and former founder/CTO. Built enterprise platforms processing hundreds of terabytes of video, GIPS-compliant investment-performance infrastructure for a $30B asset manager, and analytics systems supporting web behavior, operational reporting, and decision-making.
Experienced auditing complex systems, tracing data quality and attribution issues, defining event and reporting requirements, and turning ambiguous business questions into reliable production infrastructure. Comfortable with Google Analytics, Google Tag Manager, event-based analytics, funnel design, identity stitching, cohort analysis, and rapidly adopting platforms such as PostHog.
Core Skills
Python · SQL · AWS · Data Pipelines · Analytics Engineering · ETL · Google Analytics · Google Tag Manager · PostHog · Event Tracking · Funnel Analysis · Attribution · UTM Tracking · Dashboard Design · Data Quality · Python APIs · TypeScript · PostgreSQL · MariaDB · Docker · Terraform · GitHub Actions · Computer Vision · PyTorch · OpenCV · RLlib
Work Experience
Build production AI, reinforcement-learning, backend, and cloud systems from architecture through deployment.
- Developed DeepSlither, a reinforcement-learning agent using Ray RLlib and PPO, deployed as an autoscaled bot fleet.
- Reverse-engineered a binary WebSocket protocol and built a multiplayer server in Python and Rust within six weeks.
- Deployed containerized services through AWS Fargate and integrated cryptocurrency and fiat payment rails.
- Designed production telemetry, backend services, deployment workflows, and operational tooling for real-time applications.
- Work directly from ambiguous product requirements to architecture, implementation, testing, deployment, and troubleshooting.
Skills & Technologies: Python · Rust · Ray RLlib · PPO · WebSockets · AWS Fargate · Docker · Stripe · Solana · Backend Architecture
Founded and built an enterprise computer-vision SaaS platform for automated warehouse inventory.
- Architected the end-to-end computer-vision pipeline processing hundreds of terabytes of 5K drone video.
- Built model workflows using YOLOv8, PyTorch, OpenCV, CUDA, and Python.
- Developed the full backend and infrastructure stack across AWS EC2, Fargate, S3, RDS, Docker, MariaDB, REST APIs, and GitHub CI/CD.
- Authored internal Python libraries for database access, data processing, and pipeline orchestration.
- Converted raw drone imagery into reconciled inventory records used by enterprise customers including DHL, Toyota, CEVA, Shell, and Harley-Davidson.
- Raised more than $1M in government grants and venture funding.
- Owned product strategy, architecture, engineering, hiring, customer delivery, and investor communication.
- Utilized Support Vector Machines (SVMs) from logs of the DJI drone's raw IMU data stream using our Kotlin application.
- Trained the SVM classifier to detect anomalous telemetry patterns that indicated the drone was flying erratically, to trigger a protocol for the drone to land early.
- Trained dozens of CNN models using YOLOv8 and PyTorch to classify and detect labels and boxes in varying warehouse environments.
- Worked on SLAM (Simultaneous Localization and Mapping) techniques using combined CNN and LSTM architectures to detect moving features from drone cameras.
Skills & Technologies: Python · PyTorch · YOLOv8 · OpenCV · CUDA · AWS · S3 · RDS · Fargate · Docker · MariaDB · REST APIs · CI/CD