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Jarrell Waggoner, PhD
Biographical
email: [email protected]
Phone: 847-261-4747
Online
Website: http://www.malloc47.com
github: http://www.github.com/malloc47
LinkedIn: http://www.linkedin.com/in/malloc47
Interests
computer vision, image processing, artificial intelligence, pattern recognition & machine learning, data science, data engineering, functional programming, web development, GIS, Clojure
Summary
Engineering leader with decades-long career spanning research science, early-stage startups, and Fortune 5 companies. Specializing in the intersection of data science and data engineering with extensive experience architecting MLOps tools and data platforms. Provides technical leadership across an org-level portfolio of teams/projects while staying hands-on developing backend systems, with particular emphasis on functional languages.
Education
Aug. 2013: Ph.D. Computer Science & Engineering from the University of South Carolina
May 2009: M.E. Computer Science & Engineering from the University of South Carolina
Experience
2021---2022
Optum, Inc.
Brought in through acquisition of Rally Health, continuing as architect of the former Rally data organization now housed within the rebranded Optum Digital entity.
- Serve as Domain Workgroup Representative responsible for curating the technologies used by the data and ML practices in Optum's centralized technology governance model with influence across all of the Optum Tech organization.
- Lead an Architecture Advocates workgroup embedding architecture-focused engineers on individual teams, fostering a cross-cutting, big-picture view of our architecture across our data organization.
- Built a crawler to extract table-level data lineage from our Airflow DAGs, generating a 2000 node graph navigable through a custom-built JavaScript graph interface.
2017---2021
Architect at Rally Health, Inc.
Staff-level engineering leader responsible for overseeing technical design and engineering decisions across Rally's entire data organization that reached a peak of 90+ engineers, analysts, managers, and data scientists.
- Brought on board while Rally was a small startup to architect a complete rewrite of the data platform for the whole company, moving from a fixed Cloudera cluster to a self-service platform using Databricks and Redshift fed by Spark ETLs written in Scala and scheduled with Airflow atop Kubernetes. Built consensus on new architecture and delivered working system within a year.
- Member of the Rally Engineering Technical Staff, responsible for making cross-cutting engineering decisions, evaluating potential acquisitions, managing the RFC process, and organizing technical interest groups.
- Heavily involved in defining team structure and hiring, conducting over 140 interviews for IC and management roles to scale the data organization from 4 data engineers to over 50 data engineers across 7 teams.
- Coordinated platform integration with 20 internal and external teams and vendors across an extensive range of projects including productionalized ML workflows, frontend/mobile event tracking, real time data processing, security/compliance/privacy, data ingestion APIs, data quality validation, and self-service internal product analytics.
2016---2017
Software Engineer at DRW Holdings, LLC
Part of the Trading Infrastructure team, developing the internal platform used by every trading desk at DRW. Built greenfield high-performance service-oriented systems using Clojure and Java while maintaining legacy applications in Ruby and C# among a catalog of over 50 microservices.
- Contributed to a Ruby-based reconciliation tool used to balance cash flows for high-volume trading.
- Extended a graph-based research workflow tool used for computing the value and settle price of options, futures, equities, and other financial instruments, written in Clojure.
- Developed and extended multiple UI frontends for internal tools using React and Reagent.
2013---2016
Senior Software Engineer at Groupon, Inc.
Contributed to multiple teams solving cross-cutting data engineering and MLOps problems.
- Flux team: Responsible for a data pipeline management and machine learning platform used to run productionalized decision tree learning models to predict customer attrition, lifetime customer value, and merchant value. Spearheaded implementation of distributed systems for the feature store, job scheduling, and data catalog components used by all models on the platform. Fed from Teradata, written in Clojure, and backed by Hive.
- Supply Intelligence team: Tech lead overseeing the critical business automation of lead-to-salesperson assignment that previously required ~80 sales managers to conduct manually; led the effort to rearchitect this legacy system from an ad-hoc job scheduling platform written in Ruby and Bash to a multi-staged Hadoop pipeline written in Clojure allowing it to scale to 6M daily candidate assignments.
- Project Genesis strike team: Coordinated with product and business teams to build an ETL to inject 250K leads in Salesforce from scraped web data that increased the unassigned leads pool by 10X.
2012---2014
Technical Engineer at Huntstand, Inc.
Founding engineer at startup creating the https://www.huntstand.com web application. Written using Python, Django, and backbone.js; deployed to AWS. Responsible for curating full technology stack and coordinating with 5 developers.
2011---2013
Research Assistant funded by AFOSR
Conducted dissertation research on segmentation methods to extract important physical characteristics from image volumes of metallic and biologic materials, developed using Python, NumPy, SciPy, OpenCV, and MATLAB. Managed the lab computer network and organized weekly lab meetings. Created a Django-based web application for manual segmentation, an ML-trained classifier for assisted segmentation, and a fully automated energy-minimization segmentation approach, with large-scale evaluations on real and synthetic datasets.
2011---2013
Project Manager at Palmetto Computer Labs
Created and taught workshops on git, the Linux command line, Android development, and open source software for hundreds of students, developers, and government officials at IT-oLogy. Managed the Open IT Lab and associated projects. Assisted in planning POSSCON.
2011
Contractor for Elastic Vision Consulting
Built a parser and generator for XML medical records formats (CCR and CCD) in a Java web application. Written using JDOM, Xerces, and Hibernate, and run on an Axis2+Jetty6 driven server.
2010---2011
Research Assistant for the DARPA Mind's Eye Program
Built video event recognition systems for the DARPA Mind's Eye Program, collaborating with 10 students and faculty members across three institutions to create an AI system that describes events in a video clip as natural language sentences. Developed algorithms in Scheme, Bash, MATLAB, and C to process a corpus of 3480 videos extracted into over 1.5 million frames. Conducted distributed processing on the Steele cluster which was, at the time, among the top 500 most powerful supercomputing clusters.
2009---2010
NEH Fellow at the USC Center for Digital Humanities (Sapheos/Paragon Project)
Developed the prototype for a digital collation application as part of the Sapheos\Paragon project to identify sub-textual inconsistencies among multiple scanned copies of The Faerie Queene by Edmund Spenser. Created in MATLAB using OpenCV to process tens of thousands of book page images.
Selected Publications
[1] Derrick. C. Spell, Ling-Yong Wang, Richard T. Shomer, Bahador Nooraei, Jarrell Waggoner, Xaio-Han T. Zeng, Jae Y. Chung, Kai-Chen Cheng, and Daniel Kirsche. QED: Groupon’s ETL management and curated feature catalog system for machine learning. In IEEE International Conference on Big Data, pages 1639–1646, Dec 2016.
[2] Jarrell Waggoner, Youjie Zhou, Jeff Simmons, Marc De Graef, and Song Wang. Topology-preserving multi-label image segmentation. In IEEE Workshop on Applications of Computer Vision (WACV), pages 1084–1091, Waikoloa Beach, HI, 2015.
[3] Jarrell Waggoner, Youjie Zhou, Jeff Simmons, Marc De Graef, and Song Wang. Graph-cut based interactive segmentation of 3D materials-science images. Machine Vision and Applications, 25:1615–1629, 2014.
[4] Jarrell Waggoner. Multi-Label Segmentation Propagation for Materials Science Images Incorporating Topology and Interactivity. Dissertation, University of South Carolina, 2013.
[5] Jarrell Waggoner, Jeff Simmons, Marc De Graef, and Song Wang. 3D materials image segmentation by 2D propagation: A graph-cut approach considering homomorphism. IEEE Transactions on Image Processing, 22, 2013.
[6] Andrei Barbu, Alexander Bridge, Zachary Burchill, Dan Coroian, Sven Dickinson, Sanja Fidler, Aaron Michaux, Sam Mussman, Siddharth Narayanaswamy, Dhaval Salvi, Lara Schmidt, Jiangnan Shangguan, Jeffrey Mark Siskind, Jarrell Waggoner, Song Wang, Jinlian Wei, Yifan Yin, and Zhiqi Zhang. Video in sentences out. In Conference on Uncertainty in Arti cial Intelligence, pages 102–112, 2012.
[7] Jarrell Waggoner, Jeff Simmons, and Song Wang. Combining global labeling and local relabeling for metallic image segmentation. In Proceedings of SPIE (Computational Imaging X), volume 8296, Burlingame, CA, 2012.
Talks
[1] Project athena: Rally’s next-generation data platform. Optum/UHG/UHC Analytics Conference. Eden Prairie, MN. September 2019.
[2] Rules engines: Logic as data structure. Palme o Open Source So ware Conference. Columbia, SC. April 2015.
[3] Python for computer vision. All Things Open. Raleigh, NC. October 2013.
[4] Extending Django. Palmetto Open Source Software Conference. Columbia, SC. March 28, 2013.
Activities
data visualization, geographic information systems, Linux, music composition
Available online: http://resume.malloc47.com