Scott Gigante
Engineering Mananger at Sightline Climate
Washington, District of Columbia, United States
Summary
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SeniorScott Gigante is a Co-Founder and CTO with 11 years of experience building AI-first products and teams from prototype to revenue, most recently scaling an AI-driven climate SaaS to $3M ARR as Founding Engineer and Head of Engineering. He blends deep research pedigree (PhD-level computational biology from Yale) with hands-on engineering across ML, data engineering, devops, and backend systems, and has presented at ICLR and driven ML work used in pharma pitches. Scott has a track record of operationalizing complex models into production—implementing dimensionality reduction in Seurat, improving build/deploy tooling for NMSLIB, and maintaining global geodata quality in a widely used countries-states-cities database. Comfortable hiring and managing distributed teams across SF, NY, London and Bulgaria, he focuses on mission-driven tech—climate and biotech—and on using AI and data for social good. A detail-oriented builder, he also contributed practical DevOps fixes that enabled cross-platform wheel builds, underscoring his mix of research rigor and pragmatic engineering.
11 years of coding experience
Github Skills (19)
docker10
single-cell-genomics10
continuous-integration10
r10
dockers10
cicd10
sql10
rna-seq10
database-management10
data-analysis10
mysql9
bash9
csv8
python8
yaml7
Programming languages (16)
Github contributions (5)
nmslib/nmslib
Dec 2018 - Oct 2019
Non-Metric Space Library (NMSLIB): An efficient similarity search library and a toolkit for evaluation of k-NN methods for generic non-metric spaces.
Role in this project:
DevOps Engineer
DevOps EngineerContributions:6 commits, 4 PRs, 19 comments in 10 months
Contributions summary:Scott focused on improving the build and deployment processes of the `nmslib` repository. Their contributions involved modifying build scripts, particularly `travis/build-wheels.sh` and `travis/deploy.sh`, to support different platforms and Python versions. These changes enabled the creation of wheels and automated deployment, ensuring the project's maintainability and distribution. The user also fixed build issues related to the Appveyor build.
knnnmslibsimilarity-searchknn-searchnon-metric
satijalab/seurat
May 2018 - Jul 2018
R toolkit for single cell genomics
Role in this project:Data Scientist
Data ScientistContributions:21 commits, 5 PRs, 27 comments in 1 month
Contributions summary:Scott implemented the PHATE dimensionality reduction method within the Seurat R toolkit, enabling users to visualize high-dimensional single-cell genomics data. Their primary contribution was the creation of the `RunPHATE` function, which integrates the `phateR` package into the Seurat workflow. This involved incorporating parameters from the `phateR` package, handling data input, and integrating the PHATE output into the Seurat object for downstream analysis and visualization.
single-cell-genomicshuman-cell-atlassingle-cell-rna-seqcran
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