Stephen Huysman's CV

• Email: shuysman@gmail.com
• Location: Bozeman, MT (Remote / Open to Relocation)
• Website: www.huysman.net
• GitHub: shuysman

Skills

ML & AI: PyTorch, scikit-learn, XGBoost, Statistical Modeling, Time-Series Forecasting

Cloud Engineering: AWS (S3, Fargate, ECR, EventBridge, Step Functions, SNS, CloudWatch, VPC, IAM, Lambda), Backblaze B2, Vultr

Scientific Computing: Python (NumPy, Pandas, SciPy), R, Shell Scripting, SQL, HPC/Linux Administration

Linux Infrastructure & Storage: RHEL/CentOS, Ubuntu/Debian, NFS/AutoFS, SMB, Ext4/XFS, Btrfs, LVM, UPS Configuration (NUT), Hardware Diagnostics, Kernel Tuning

Networking: iptables/firewalld, DNS, VLANs, VPN (OpenVPN, WireGuard, Tailscale), SSH

Data Engineering: Docker, Ansible, Git, cloud-init, Automated Workflows, Distributed Systems, Parquet

Virtualization: VMware, Hyper-V, QEMU/KVM

Databases: MySQL, MariaDB, SQLite, PostgreSQL

Web Development: Django, Flask, nginx

HPC & Distributed Computing: Slurm, Sun Grid Engine, GNU Parallel

Geospatial Computing: Python (GeoPandas, Rasterio, PyQGIS, Xarray), R Spatial (terra, sf, raster, rayshader), QGIS, ArcGIS, netCDF, THREDDS, CDO

AI-Assisted Development: Claude Code, Gemini-cli, gptel, Aider

Domain Expertise: Environmental Modeling, Habitat Assessment, Ecological Forecasting

Document Preparation: LaTeX, Typst, org-mode, Markdown

Amateur Radio: FCC Technician Class License, Callsign KK7PBI

Experience

Data Management/Scientist, Northern Rockies Conserv. Coop. -- Bozeman, MT

June 2024 – present

• Architected a fault-tolerant, high-throughput geospatial forecasting system processing large scientific data sets across distributed containerized infrastructure (Docker/AWS).

• Designed automated workflow orchestration for multi-stage modeling pipelines, implementing failure recovery logic and dynamic resource provisioning to optimize compute costs.

• Deployed and operate data-driven monitoring tools to analyze system performance, track data processing activities, and optimize resource utilization.

• Owned full technical lifecycle: ETL pipeline development, containerization, deployment architecture, monitoring, and iterative improvements based on stakeholder feedback.

• Developing PyTorch-based LSTM model for streamflow forecasting, synthesizing meteorological inputs and stream gauge records into unified training tensors.

Graduate Research & Teaching Assistant, Montana State University -- Bozeman, MT

Aug 2022 – June 2025

• Developed high-resolution geospatial models for climate refugia mapping, utilizing hydrologic water balance modeling, wildfire danger assessment, and disease probability.

• Created automated GIS workflows to accelerate identification of optimal planting microclimates for whitebark pine restoration, processing large-scale climate and topographic datasets.

• Built custom R packages for spatial analysis and modeling, integrating multiple environmental data sources (climate, topography, disturbance history) for conservation decision-making.

• Led 4 undergraduate laboratory sections for Plant Systematics and Seed Plant Identification, teaching approximately 25 students per semester through practical exercises and lectures.

Biological Science Technician, National Park Service -- Brooklyn, NY

Mar 2022 – July 2022

• Conducted surveys for threatened plant and shorebird species, collecting field data to support population trend analysis, habitat assessment, and conservation reporting.

Riparian Botanist, Great Basin Institute -- Bend, OR

May 2021 – Oct 2021

• Led botanical surveys on public lands to monitor native and invasive plant communities, assess ecosystem health, and inform land management decisions across remote backcountry locations.

Senior Programmer/Analyst, Stony Brook Medicine -- Stony Brook, NY

Jan 2019 – May 2021

• Administered a 192-core HPC cluster, migrating departmental research workflows to the university Slurm cluster using Singularity containerization.

• Managed the computing environment and full hardware lifecycle, including provisioning and maintaining physical servers and virtual machines.

• Implemented a cloud-based, HIPAA-compliant disaster recovery strategy for a 120TB clinical research data network share (NFS), utilizing automated daily backups and integrity verification.

• Provided technical leadership to student programmers, establishing standard development practices, code reviews, and version control workflows (Git) to ensure reproducibility.

• Developed Django web applications for HR and research data management, serving approximately 50 faculty with secure handling of sensitive compensation and evaluation data.

Education

Montana State University, M.S. in Biological Sciences -- Bozeman, MT

2022 – 2025

• Thesis: Mapping Climate and Disturbance Refugia for Conservation of Whitebark Pine

Cornell University, B.S. in Plant Sciences, cum laude -- Ithaca, NY

2007 – 2011

• Activities: Theta Delta Chi Beta Charge

Conference Presentations

2025 Whitebark Pine Ecosystem Foundation Conference -- Wildfire Ignition Danger: Strategic Projections and Tactical Forecasts

2025 Whitebark Pine Ecosystem Foundation Conference -- Planting microsite selection using a high-resolution water balance model

2025 Today's Voices of Conservation Science Podcast -- Whitebark Pine In A Changing Climate: Where Will They Survive

Projects

climate-wildfire-ecoregions

github.com/shuysman/climate-wildfire-ecoregions

• Production data pipeline for wildfire ignition forecasting deployed on AWS with containerized architecture

streamflow-nn

github.com/shuysman/streamflow-nn

• PyTorch LSTM model for hydrological forecasting with multivariate time-series inputs

nps-microclimate-water-balance

github.com/shuysman/nps-microclimate-water-balance

• High-resolution (1m) gridded water balance model for planting microsite selection