Matt Wimer:
Location: Remote, Oregon, USA
Contact: [login to view URL]
LinkedIn & GitHub: /matthew-wimer-3ba41114 | /subsilico
Summary:
I'm a seasoned Software Architect with 20+ years in the tech industry, specializing in AI, machine learning, and statistical programming. I've led pivotal projects like the CylantSecure, recognized twice as LinuxWorld's "Best Security Product", and spearheaded AI integrations at Subsilico.
Experience Highlights:
Subsilico (2017-Present): Developed AI/ML systems; integrated statistical programming to enhance industry applications.
Gladstone Institutes (2016-2017): Engineered statistical models for neurological data analysis using Matlab, Perl, C, and R.
Crescendo Bioscience (2011-2014): Optimized Clinical Data LIMS with statistical techniques.
Cylant (1999-2003): Innovated anomaly detection in Linux Kernel security, leading to major accolades.
Skills:
Statistical Programming: R, SAS, MATLAB, Python.
Languages: C, C++, Perl, Python, Java, JavaScript.
Systems/Platforms: Expert in Linux/UNIX, proficient in AWS.
Databases: SQL, PostgreSQL, MySQL.
Objectives:
Looking to apply my statistical programming prowess and software development expertise in challenging projects requiring innovative solutions.
Key Projects:
ecomplexity & centroids on GitHub: Advanced statistical algorithms and anomaly detection.
Driven to leverage deep statistical insights and software architecture knowledge for impactful projects.