Govinda Dhungana

Lead Data Scientist

Dallas-Fort Worth Metroplex United States
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Summary

👤
Senior
🎓
Top School
Govinda Dhungana is a Lead Data Scientist with 11 years of experience applying physics-trained quantitative rigor to large-scale data systems, from astronomical survey pipelines to nationwide telecommunications analytics. He designs and ships end-to-end data processing and calibration pipelines, integrates QA metrics and Bayesian/graph-based inference for root-cause diagnostics, and has a demonstrated 20% efficiency gain from image-processing methods developed during his PhD. At AT&T he blends big-data engineering (Spark, Hive, Kafka) with ML, survival and time-series modeling to reduce avoidable dispatches and enable real-time network trouble detection, and previously built spatial and demand-propensity prediction products at SMU DataArts. Known for cross-functional delivery and maintaining production-grade codebases, he pairs deep domain knowledge in experimental astrophysics with practical productization skills that turn research ideas into operational tooling. Based in the Dallas–Fort Worth area, he brings a unique mix of scientific modeling, software engineering and project leadership to complex, noisy-data problems.
code11 years of coding experience
job7 years of employment as a software developer
bookMaster of Science - M. Sc., Physics, Master of Science - M. Sc., Physics at Tribhuvan University, Central Department of Physics
bookMaster of Science - MS, Physics, Master of Science - MS, Physics at Southern Methodist University
languagesHindi, English, Nepali
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Github Skills (12)

pipeline10
spectral10
photosphere9
simulation8
simulations8
python4
astronomy3
catalog3
image-processing2
supernova2
computer-vision2
osc1

Programming languages (3)

JavaScriptJupyter NotebookPython

Github contributions (5)

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rotsehub/ImageDiff

Aug 2016 - Oct 2017

Contributions:1 release, 17 commits, 1 push in 1 year 1 month
gdhungana/desispec

Feb 2015 - Sep 2016

Contributions:4 PRs, 29 pushes, 29 branches in 1 year 7 months
spectralpipelinedesi
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