Teaching EMSE 4197: Analytical Methods for Engineers for AI/ML doctoral students at the George Washington University (GWU), which focuses on the understanding of the programming language Python and its application in artificial intelligence and machine learning.

• Technical lead and project manager across multiple contracts related to data science, softwareengineering, modeling and simulation, and data engineering tasking in support of the Departmentof Defense (DoD)• Implemented a sensitivity analysis to direct time and effort across divisions regards to information gathering and modeling• Manage several teams of subcontractors, as well as directly managing internal colleagues, across varying levels of classified contracts by coordinating tasking, implementing an agile/scrum working environment, and providing technical contribution to each delivered project• Leading the technical research and proof-of-concept creation ahead of project kick-offs in orderto discover new/novel tools, techniques, and methodologies to solve niche problem sets• Heading the recruiting effort to staff contracts and create technical onboarding processes to bring new hires up to speed on technologies relevant to each customer• Technology and related skills include Python, AWS Sagemaker, Docker, NiFi, Tensorflow,Pytorch, Weights & Biases, Sensitivity Analysis, Graph Neural Networks (GNNs), and Modeling & Simulation, Large Language Models (LLMs)

• Own the technical relationships between Labelbox and our federal customers to includecontractors, system integrators, and state/federal government agencies• Assist in the adoption of the Labelbox platform – both from an infrastructure and usabilityperspective• Work with customers to develop solutions for their computer vision (CV) and natural languageprocessing tasks (NLP), including ontology development, training data curation, model training,and model diagnostics• Provide a medium through which customers can relay feature requests and bug reports in order toimprove the Labelbox platform and mold our tool to the needs of our federal customers• Support installations of the platform in both unclassified and classified environments• Develop scripts and models in order to provide proof of concepts (POCs) to support salesengineering• Technology and related skills include Python, Huggingface, Labelbox SDK, GCP, Replicated,Kubernetes, Tensorflow, and Pytorch

• Leading multiple data science projects/teams concurrently that revolve around implementing computer vision (CV), natural language processing (NLP) and pattern-of-life techniques• Assist in writing and debugging code, testing pre-built functionalities, and researching methodologies in order to implement and solve new requirements. NLP related tasking included document preprocessing/applying optical character recognition (OCR), topic modeling, and name-entity-recognition (NER). CV related tasking included creation and evaluation of object detection, segmentation, and classification models• Assist in adopting the AWS platform into the team’s working environment which resulted in model development and deployment time-savings. Adapted previously developed applications to the AWS environment.• Implemented an agile work environment within separate teams on staggering project cycles and coached the division on data science/consulting/branding fundamentals in order to enhance productivity and create a distributed workload. Provided guidance into data science best practices and successfully brought in new technologies to satisify unmet organizational needs (model repositories, ETL tools, labeling tools, etc). Defined required data science competencies and developed a 5-year training plan that is currently being implemented by the division• Technology and related skills include Python, Pytorch, Huggingface, Spacy, R, AWS Sagemaker/ECR, Docker, Harbor, GitLab, ArcGIS Pro, and Linux

• Accountable for creating a deep-learning object detection pipeline that utilizes an HPC/Slurm multi-GPU environment. Full pipeline consists of ingesting satellite imagery, labeling imagery and/or video, preprocessing and augmenting of images, model-training in different deep-learning frameworks, creating an automated program for inference across a cluster of 10 nodes, and outputting the results to visualization tools. Techology and related skills include LabelBox, Roboflow, Python, Linux, Slurm, Tensorflow, Pytorch, OmniSci, Elastic Search, and Kinetica.• Coordinated weekly meetings between our team and vendors such as NVIDIA, Roboflow, and OmniSci in order to troubleshoot and resolve issues or set up workshops in order to advance projects and related knowledge.• Responsible for presenting/live demoing the object detection pipeline to GDIT and NGA leadership, as well as incorporate feedback, provide proof of concept, future plans, and project schedules.

• Reported directly to the VP of Marketing Intelligence. Responsible for defining project scopeand timelines, as well as providing updates to the business. Created presentations anddelivered the learnings/recommendations to the executive team and Driven Brands businesssegments. Utilized Google Cloud Storage, Google BigQuery, R, Python, and Alteryx.• Lead the effort of analyzing the Digital Marketing Platform (DMP) by working inbetweenSalesforce and the Driven Brands Digital Marketing team. Implemented Markov Chainanalysis to find optimal digital touchpoint paths in order to optimize digital cost-savings anddefine device targeting strategy for each audience of customers.• Lead the analytical effort of providing fleet health metrics to the Driven Brands Fleet team ona monthly basis, as well as for adhoc requests. Preformed clustering analyses of differentbrand’s shops across the U.S. to discover patterns and optimal attribution in order to createbaseline targets for 2020 shop strategies. Created processes to ingest third-party data in orderto perform fleet penetration analysis. Created Python scripts to automate the process ofreverse address lookups in order to append additional business information via Google APIs.• Combined COVID-19 variables, macro variables, and attributes created in-house to forecast sales for the remainder of 2020 in order to analyze the affect of the virus on businesses.

• Responsible for the entire data management life cycle of a commercial excellence programthat reports directly to the CEO of Honeywell. The life cycle includes the aggregation andconsolidation of data from various sources – both internal and external, ETL of data viasoftware workflows as well as SQL manipulation, the management of landing tables within adatawarehouse, and the ownership of the sources and security of a data visualization platformthat supplies 100+ users• Performed initial data quality assessment and exploratory data analysis as a separatedeliverable to leadershipSteven Cocke• Created initial machine learning classifer/regresser models for predictive analytics usingpython and integrated it with ETL workflows. Models were both supervised andunsupervised.

• Execute business and technical roles for Data Quality and Data Integration projects bydelivering and implementing scalable and high-performing solutions for major banks,healthcare, and manufacturing companies• Lead meetings with customer department managers and directors to guide them with theconfiguration and the architecture of their solutions on how to best meet their businessrequirements and data stewardship activities, as well as provide knowledge transfer• Prepare and present both detailed and high-level product demonstrations and technicaldocumentations, ranging from installations to product capability demos, for customers fromdifferent departments and skill backgrounds• Work alongside senior consultants, customers, and business partners both on short-term andlongterm engagements, to provide high quality and efficient Informatica expertise inaccordance with customer expectation

• Implemented Informatica Data Integration, Data Quality, and Master Data Managementsoftware, a set of ETL (Extract, Transform, Load) tools, that allows large sets of data to becleaned, transformed, and warehoused – dramatically cutting overhead costs and improvingbusiness processes for customers• Developed and unit tested mappings and workflows, which are responsible for sendingmillions of records from the source table to final base object table, according to functionaldesign specifications – Operating systems: Windows, Linux; Databases: SQL Server, Oracle,AmazonS3; Languages: SQL, Java• Worked on an internal project that involved creating an Informatica Cloud HealthcareAccelerator• Participated actively on Informatica product enablement, whether it was learning a newproduct or a new version of a product, to acquire new knowledge or to stay up-to-date withsoftware patches and releases

• Assisted Navy program’s compliance with Military Standards (MIL-STD) and otherrequirements/directives that defined and guided Program Managers (PMs) in ordnance withsystem safety that had to be met to field their respective systems• Seeked approval for projects from the Weapon Systems Explosives Safety Review Board(WSESRB) and the Naval Ordnance Safety and Security Activity (NOSSA)