Hello, my name is Aaron Kanzer! I am currently the founder of Scigantic. While not at work, I am also currently the Green Monster Scoreboard Operator at Fenway Park. I received my Master's of Science in Computer Science with a specialization in artificial intelligence at Northeastern University in 2020. Before graduate school, I was the 2016 Democratic Nominee for MA State Representative in the 2nd Barnstable District. My other experiences include being a policy aide for the Massachusetts Bay Transportation Authority, as well as an appointed member on the Barnstable Housing Committee. In my spare time, I serve on the Boston Healthcare for the Homeless Program Emerging Leaders Board. I enjoy playing tennis and practicing guitar. Click here for a copy of my resume: PDF
In 2026, I founded Scigantic, Inc., building a platform for exploring large-scale, open-source, cloud-agnostic datasets and democratizing the fine-tuning of models across multiple scientific domains. I crafted custom agentic tooling for JupyterHub interactions with Claude, GPT, and AWS Bedrock, and led the go-to-market strategy for distribution across academic labs and biopharma.
In 2025, I joined Generate:Biomedicines as a senior software engineer on ML Operations. I replicated AlphaFold3 model training to fine-tune diffusion models for protein design, supported large-scale structure prediction submissions against open-source models, and configured CPU- and GPU-optimized pipelines to support tooling across protein design.
In 2023, I joined the McGovern Institute for Brain Research as a research software engineer. I've been the founding full-stack engineer for the LINC project, an initiative to map neural circuits in the brain. The platform is built in consortium with 9 other academic institutions.
In 2022, I joined the Broad Institute as a senior software engineer. I've worked on the Terra project, an open-source software platform for genomics research. The platform is built in partnership with Microsoft and Google.
In 2019, I joined PathAI as a software engineer. I've worked on FDA-related clinical projects, supporting full-stack, site reliability and infrastructure work to manage our machine learning algorithms.
Since 2017, I have worked as a Green Monster Scoreboard Operator at Fenway Park. I was fortunate enough to work the 2018 World Series, and have given tours of the scoreboard to a lot of fun and unique people over the years.
Under the advisement of Professor Peter Tarasewich, I helped tutor and create course materials for graduate and undergraduate students taking courses in information visualization and data analysis. I also assisted the department with researching emerging trends in business analytics.
At the age of 21, I ran for the Massachusetts State Legislature within my hometown on Cape Cod. After knocking on over 8,000 doors personally, my campaign won a heavily contested primary and received 45% of the general election vote. My campaign was also endorsed by many elected officials and national advocacy groups.
During graduate school, I worked as a web designer with SignedOn on an ad hoc basis. Most of my work at SignedOn entailed building static webpages with WordPress plug-ins, as well as cleaning and writing custom CSS Code.
In 2014, I worked as a Policy Aide at the Massachusetts Bay Transportation Authority. My work included conducting economic analyses on inventory and service-related issues, as well as writing SQL script queries to obtain empirical evidence for my projects.
Northeastern University - Master's of Science - Computer ScienceGraduated April 2020 Specialization in artificial intelligence
Northeastern Unviersity - Bachelor's of Science - Economics & Political ScienceGraduated May 2016
United Nations Institute for Disarmament Research - Research SponsorshipSummer 2013Specialization in humanitarian affairs and conflict negotiationLocated at United Nations Offices in Geneva, Switzerland
Programming Languages: Expertise in Python, Java, and Typescript/Javascript, Golang, Rust Infrastructure / DevOps: Kubernetes, Docker, Helm, Pulumi, Terraform, nginx Applied AI: agentic workflows, fine-tuning model development, protein design, computer vision