Alan Penkar

Director - Machine Learning Engineering (Staff) at Manhattan Associates

Atlanta Metropolitan Area United States
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Summary

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Senior
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Top School
Alan Penkar is a Director of Machine Learning Engineering with a decade of experience building and scaling ML and analytics teams across enterprise and consulting environments. Currently leading ML engineering at Manhattan Associates after progressive technical leadership roles including Senior Principal ML Engineer and Lead Data Scientist, he blends operational delivery with research-backed analytics from his Georgia Tech MS in Analytics and BS in Applied Mathematics. He has deep hands-on experience in productionizing models, workforce and data integrations, and mentoring cross-functional teams to translate complex requirements into reliable, auditable systems. An active contributor to robotics software (notably improvements to Georgia Tech RoboJackets' RoboCup Small Size League codebase), he brings practical algorithmic problem solving and clean code sensibilities to real-world products. Based in Atlanta, he pairs consulting rigor with product-focused execution to drive measurable business impact.
code10 years of coding experience
job7 years of employment as a software developer
bookMaster of Science - MS, Analytics, Master of Science - MS, Analytics at Georgia Institute of Technology
bookHigh School Diploma, High School Diploma at Greenhill School
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Github Skills (8)

smallbasic10
smalltalk10
robotics10
python10
data-structure9
algorithm9
data-structures9
algorithms9

Programming languages (7)

TypeScriptC++ShellJavaScriptHTMLApacheConfPython

Github contributions (5)

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RoboJackets/robocup-software

Jan 2019 - Jul 2019

Georgia Tech RoboJackets Software for the RoboCup Small Size League
Role in this project:
userBack-end Developer
Contributions:54 commits, 6 PRs, 34 pushes in 5 months
Contributions summary:Alan primarily focused on improving the codebase related to the RoboCup Small Size League. Their contributions included extensive commenting and documentation updates for the `mark.py` skill and the `submissive_defender.py` tactic. Further, they developed and refined the `goalside_mark.py` skill, addressing issues related to shot evaluation and goal zone intersections using Cohen-Sutherland line clipping. They also made code refactoring, especially within the goalside mark code and added new functionality for rect intersection.
roboticssmall-sizerobojacketsgeorgialeague
Contributions:2 PRs, 39 pushes, 4 branches in 1 year 2 months
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Alan Penkar - Director - Machine Learning Engineering (Staff) at Manhattan Associates