With 15 years of experience in building, maintaining, and decommissioning systems for trading, investing, new product development, analytics, reconciliation, and model lifecycle management, I've worked across funds, startups, and scale-ups with assets under management ranging from $3M to $500B. My expertise lies in both Traditional Finance and Decentralized Finance, focusing primarily on data-intensive aspects of the technology stack.
My architectural specialties usually involve data pipelines, abstraction layers, distributed systems, schedulers, clusters, experiments, and client-server patterns. These are used as an arsenal to adjust the net present value associated with technical changes. Thats what get me excited; aligning an organization's risk profile and cost of capital to the pace and decisions of software development.
I tackle challenging problems and embrace new technologies with an ownership mindset. I prefer taking risks to remaining passive. My decision-making process is geared towards making quick, reversible, and defendable choices. I advocate for data, money, technology and networks that are open, interconnected and programmable. I strategically invest in specific trends rather than diversifying.
Python is my tool of choice, having contributed to significant projects like Pandas and Counterparty starting in 2014. My experience is broad, ranging across the modern data stack, from S3 to Snowflake, PostgreSQL to Spark, AWS, GCP, Kubernetes, Airflow and Docker.
Via e-mail using firstname.lastname@gmail.com or talk to my AI assistant.