Robert Streetman

robert.streetman@mailfence.com

Sr. Software Engineer

I’m a senior software engineer focused on building data-driven and machine-learning-powered applications that solve real, messy problems. My background spans applied machine learning, scientific computing, and large-scale production systems. Early in my career, I implemented clustering algorithms, normalization techniques, and stochastic models in Java for academic and government research. That foundation gave me a strong appreciation for model behavior, data quality, and the tradeoffs between theory and real-world constraints. In the finance sector, I’ve worked on enterprise applications supporting critical business workflows, where I regularly diagnose complex failures across APIs, data pipelines, and application code. While this role has been operationally focused, it has sharpened my ability to reason about production systems, debug difficult issues, and design software that behaves predictably under pressure. I’m seeking a software engineering role centered on machine learning applications, where I can design, implement, and evolve systems that turn data into usable features and products.

Experience

S&P Global

Sr. Software Engineer • May, 2018 — Present

  • Worked on a custom content-authoring and publishing platform used to transform analyst-authored documents into structured, web-published content at enterprise scale.
  • Specialized in diagnosing and resolving failures caused by highly variable, semi-structured inputs originating from Microsoft Word and Excel, including complex document markup, embedded objects, and inconsistent authoring patterns.
  • Performed deep analysis across application layers (document structure, REST APIs, transformation logic, and downstream services) to identify systemic patterns in content ingestion failures.
  • Designed and prototyped Python-based automation and validation scripts to classify problematic content patterns, reduce manual triage, and explore rule-based and data-driven approaches to preprocessing and normalization.

Colorado State University

Research Associate • May, 2013 — Aug, 2017

  • Coded new modules for a scientific model in Java, such as simulating soil moisture, water quality, and grassland growth.
  • Integrated a legacy Fortran model into a larger Java-based framework.
  • Coded Java web services to process GIS and weather data.

Louisiana State University in Shreveport

Graduate Assistant • Aug, 2012 — Dec, 2012

  • Coded the naive k-means clustering algorithm in Java using peer-reviewed publications for reference.
  • Coded normalization methods using different distance measurements (min-max, Manhattan/L1, Euclidean/L2, etc), used to compare the effects of normalization on the clustering outcome.
  • Coded the sum of square errors metric to validate the cluster performance, and ran validation on a subset of the UCI ML Repository collection.

Education

Louisiana State University in Shreveport

Master of Science, Computer Systems Technology — Computer Science concentration • 2009 — 2012

Graduate Assistantship — The effect of normalization on the performance of the k-means clustering algorithm.

Louisiana State University

Bachelor of Arts, English Literature; German minor • 2003 — 2007

Projects

Developer • Feb, 2026 — Present

Estimate pepper (Capsicum sp.) growth with simple models using local weather data.

Certifications

AWS Certified Machine Learning Engineer - Associate

Amazon Web Services • Oct, 2025

Credential ID 42c5c4a32c744a9eae4bf35e4184d806

AWS Certified AI Practitioner

Amazon Web Services • Sep, 2025

Credential ID 2186dada-9b7d-472f-b826-b33daa6e75ea

AWS Certified Solutions Architect - Associate

Amazon Web Services • Aug, 2020

Credential ID JX8ZMW0CHFR11J9R

Certified Associate Python Programmer [PCAP-31-03]

OpenEDG Python Institute • Sep, 2025

Credential ID Z3Mt.Ddeo.jjC4

Open Water Diver

PADI • May, 2011

Credential ID 11050Z6019

Social Links

  • Github: https://github.com/rstreet85
  • LinkedIn: https://linkedin.com/in/robertstreetman