Awesome-CV/original.tex

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{\small\begin{tabular}[c]{l}
  Abu Dhabi, UAE\\
\href{https://datavistics.github.io}{https://datavistics.github.io}
\end{tabular}}\hfill%
{\Large\bfseries\begin{tabular}[c]{c}
  Derek Thomas
\end{tabular}}\hfill%
{\small\begin{tabular}[c]{r}
  PN: +971 56 997 0806 \\
  \href{mailto:datavistics@gmail.com}{datavistics@gmail.com}\\
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\begin{resume}

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%	OBJECTIVE SECTION
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\section{PROFILE SUMMARY}
AI Solutions Architect with 10+ years of experience, passionate about using AI use-cases for actual production. Skilled in Generative AI, LLM Deployment \& Inference, Technical Communication, Champion Building, and Applied Engineering. I excel in roles that blend research, engineering, and real-world impact through customer enablement.

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%	PROFESSIONAL EXPERIENCE SECTION
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\section{EXPERIENCE}
{\textbf{Machine Learning Success Engineer}} \hfill December 2022 - Present\\
\href{https://www.huggingface.co/}{Hugging Face (World-leading Open-source AI Unicorn)} \hfill Abu Dhabi, UAE\\
Role: Drive AI adoption by technically qualifying HF to business prospects and supporting enterprise customers.
\begin{itemize} \itemsep -2pt
\item Drove Hugging Face’s largest-ever quarter (Q1 2024), by single-handedly supporting Account Executives to achieve 120\% of the team goal
\item Advised teams on cost-efficient Foundational Model strategies, including Inference Optimization, Quantization, and Compact Model adoption.
\item Publications \& Research: Authored technical blogs on \href{https://datavistics.github.io/posts/arabic-rag-1/}{Arabic RAG}, \href{https://huggingface.co/spaces/derek-thomas/fawkes}{Speech-to-Speech}, \href{https://huggingface.co/spaces/derek-thomas/fawkes}{Multi-LoRA Inference}, and \href{https://datavistics.github.io}{more}
\end{itemize}

I have guided teams (from startups to Fortune 500) on diverse GenAI use-cases:
\begin{itemize} \itemsep -2pt
\item Designed solutions in Agentic Workflows, prompt engineering, synthetic data generation, and LLM evaluation for Finance, Healthcare and other applications.
\item Fine-tuned LLMs for document summarization, code-gen, automated reporting and domain specific Agentic RAG (leveraging PyTorch/Hugging Face)
\item  Deep experience in \href{https://huggingface.co/blog/billion-classifications}{profiling large scale inference}
\end{itemize}

I have helped pioneer new AI products in our platform
\begin{itemize} \itemsep -2pt
\item HUGS - production-ready, optimized zero-configuration inference microservices to accelerate deployment
\item SafeCoder - Self-hosted, compliant code-gen solution fine-tuned on your private code
\end{itemize}

I embody broad skills
\begin{itemize} \itemsep -2pt
\item Thought Leadership: High-impact speaker at global AI conferences, including GITEX in Dubai and major events in Seoul and Singapore.
\item Cross-Functional Communication: Bridged technical and non-technical discussions with C-suite, engineering, and research teams to drive AI project delivery
\item Team Growth \& Leadership: Spearheaded recruitment efforts, growing the ML Success team by 300\%
\end{itemize}

{\textbf{Customer Facing Data Scientist}} \hfill November 2021 - September 2022\\
\href{https://www.datarobot.com/}{DataRobot} (AutoML Platform) \hfill Abu Dhabi, UAE\\
As the first Data Scientist in the Middle East, I tailored Customer Success strategies to meet local needs differing from the more established frameworks in the US and Europe.

Spearheaded DataRobot compatibility with Hugging Face
\begin{itemize} \itemsep -2pt
\item Conducted largest partner \href{https://www.datarobot.com/webinars/getting-started-with-transformers-and-mlops/}{webinar} with Hugging Face in DataRobot history
\item Pioneered AutoML and MLOps monitoring with Transformers (text drift, concept drift)
% \item Developed first Real-Time Speech app in DataRobot using \href{https://huggingface.co/facebook/wav2vec2-base-960h}{Hugging Face's Wav2Vec2}
\item Led DataRobot's first client enablement session with Transformers
\end{itemize}

Drove end-to-end AI Solutions with teams of varying maturity in diverse industries
\begin{itemize} \itemsep -2pt % Reduce space between items
\item Delivered 20+ Use Cases from framing to production across 10 clients
\item Developed specialized training and provided on-going Data Science up-skilling
% \item Expand on HP Tuning Model Factories
% \item Integrated deployed models with client systems to maximize business impact
\item Empathized with customers to build champions at multiple levels
% \item MLOps find one
\end{itemize}

Made a strong impact with many use-cases across diverse industries
\begin{itemize} \itemsep -2pt
\item Banking: Propensity models \& Next Best Offer boosted conv. rate 5x-13x per product
% \item Banking: Churn reduced by 35\% in the first year
\item \href{https://www.datarobot.com/customers/oyak/}{Manufacturing}: Machine efficiency \& Material Quality UC drove \$1.6M in savings/yr
\item \href{https://www.datarobot.com/wp-content/uploads/2022/01/DataRobot_CustomerSuccessStory_OYAK.pdf}{Green AI}: Reduced CO2 emissions nearly 200,000 tons per year
\item Utilities: Solar Generation, Materials Demand Forecasting, Payment Default et. al.
% \item Retail: Demand Forecasting and Price Optimization for various products
% \item Tech: Time Series Anomaly Detection for Hardware Sensors
\end{itemize}

{\textbf{Lead Data Scientist/Lead Data Engineer}} \hfill February 2021 - September 2021\\
UAE Government Contractor \hfill Abu Dhabi, UAE\\
Team Lead: Built a hybrid cloud Big Data platform processing 6M docs/day.
\begin{itemize} \itemsep -2pt % Reduce space between items
% \item Replaced industrial 65 language NLP and geoparsing/geolocation solution with in-house models  to save \$700,000
\item Replaced legacy NLP/Geoparsing vendor solutions with Transformers to save \$1.3M
\item Improved 20\% recall (sentiment); 23\% accuracy (NER); Averaged across languages
\item Managed data vendor relations and created an engineering solution to save \$600,000
% \item Created 3 products specifically focused on increasing customer AI trust
% \item Technical Emiratization - Mentored new-grad to design first production data pipeline
\end{itemize}

{\textbf{Senior Data Scientist}} \hfill April 2019 - February 2021\\
\href{https://g42.ai/}{G42} (AI Startup → Unicorn) \hfill Abu Dhabi, UAE\\
Machine Translation (Pre-training): Arabic $\leftrightarrow$ English
\begin{itemize} \itemsep -2pt % Reduce space between items
\item Performance competitive with Google:  $\pm $3 BLEU Points depending on the domain
\item Led Data Engineering/Cleaning: 78\% of the BLEU improvement from initial model
% \item Implemented SotA cleaning techniques: Back-Translation and Bi-cleaner
\item Created a fast, parallel, data cleaning pipeline with Apache Airflow: 24B sentences
\end{itemize}

News Information Extraction
\begin{itemize} \itemsep -2pt % Reduce space between items
\item Dynamic knowledge graph to inter-connect streaming news data with 40K articles/day
% \item Published Research Papers at CIKM, ACL, SIGIR 2020
\item Implemented and improved SotA Entity Linking models to be compatible with BERT
% \item Project Management: Facilitated customer discussions and product shaping
% \item Conducted extensive Entity Linking literature review
\end{itemize}
Mixed Language (Arabic/English) High Noise OCR
\begin{itemize} \itemsep -2pt % Reduce space between items
% \item Dealt with very noisy, diverse domain, mixed language (AR, EN) data
\item Developed adaptive localized binarization filter in pytorch which improved bounding box recognition and decreased character error rate by 50\%
\end{itemize}

{\textbf{Data Scientist}} \hfill March 2018 - April 2019\\
\href{http://saal.ai/}{Saal.ai} (AI Startup) \hfill Abu Dhabi, UAE\\
Oil Price Prediction - 7 day forecasting
\begin{itemize} \itemsep -2pt % Reduce space between items
\item Cleaned and feature engineered, diverse time-series data of varying frequencies
% \item Utilized Tree Parzen Estimators for Bayesian hyper-parameter optimization
\end{itemize}
Developed NLP/AI functionalities and deployed as a Dockerized REST Microservice:
\begin{itemize} \itemsep -2pt % Reduce space between items
\item Stance Detection using BERT based Semantic Distance metrics
\item Led research in Graph Attention Networks for Text Classification
\end{itemize}

{\textbf{Data Analyst; Systems Engineer; FPGA Engineer}} \hfill January 2014 - December 2017 \\
Rockwell Collins (Government Avionics) \hfill Cedar Rapids, Iowa, USA\\
\begin{itemize} \itemsep -2pt % Reduce space between items
% \item Sold senior leadership on plans with estimated 20\%+ cost savings for 7 programs
\item Developed a real-time data model which led to over \$15,000 of savings the first week
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%	PUBLICATIONS SECTION
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% \vspace{-5mm}
\section{PUBLICATIONS}
\textbf{\href{https://arxiv.org/abs/2008.00441}{Relation Extraction with Self-determined Graph Convolutional Networks}} \\SK Sahu, D Thomas, B Chiu, N Sengupta, M Mahdy\hfill  CIKM 2020 \\
\textbf{\href{https://aclanthology.org/2020.acl-main.366.pdf}{Autoencoding Keyword Correlation Graph for Document Clustering}}\\B Chiu, SK Sahu, D Thomas, N Sengupta, M Mahdy  \hfill ACL 2020 \\
\textbf{\href{https://dl.acm.org/doi/10.1145/3397271.3401203}{Attending to Inter-sentential Features in Neural Text Classification}}.\\B Chiu, SK Sahu, N Sengupta, D Thomas, M Mahdy  \hfill SIGIR 2020 \\
% \textbf{\href{https://oeis.org/A051843}{5th Dimensional Octagonal Based Pyramidal Numbers}} \hfill June 2007\\
% Just out of high school, I derived the generating formula for this figurate number sequence.
\vspace{-5mm}
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%	Technology SKILLS SECTION
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% \section{SKILLS}
% {\sl Customer Success:} Experienced in diverse cultures, Can communicate to technical and non-technical audiences, Strong relationship builder\\
% {\sl Machine Learning:} Transformers, Sentence Embeddings, NLP, Deep Learning, Hyper Parameter Optimization\\
% {\sl Big Data:} Apache Airflow, PySpark, Elasticsearch, Kibana, AWS Solutions\\
% % {\sl Engineering:} Docker, Singularity, Flask, Git, DVC, GraphQL\\
% {\sl Technologies:} Hugging Face, Pytorch, Pandas, Sci-kit Learn, Neo4j, Torchserve\\
% %{\sl Visualization:} Plotly, ggplot2, Matplotlib, d3, Vega\\
% % {\sl Misc:} OCR, Data Cleaning, Feature Extraction, Regular Expressions
% \vspace{-5mm}

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%	EDUCATION SECTION
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\section{EDUCATION}
{\textbf{University of Louisville}} \hfill Louisville, Kentucky, USA\\
{MEng Electrical and Computer Engineering}  \hfill December 2011 - December 2012 \\
{\sl Magna Cum Laude + Honours} \hfill GPA: \textbf{4.0}\\
{BSc Electrical and Computer Engineering}  \hfill August 2007 - December 2011 \\
{\sl Mathematics Minor} \hfill GPA: \textbf{3.6}
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%	Co-Op SECTION
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\vspace{-5mm}
% \section{CO-OP/INTERN}
% {\textbf{Air Force Research Labs}} \hfill Rome, New York, USA\\
% {Electronic Communications Research}  \hfill May 2012 - August 2012\\
% %\begin{itemize} \itemsep -2pt % Reduce space between items
% %\item Lead and coordinated discovery phase experimentation
% %\item Researched use of alternative signal spaces for Hybrid Networking
% %\item Top choice by professor - only 1 a year gets chosen
% %\end{itemize}
% {\textbf{Federal Bureau of Investigation}} \hfill Quantico, Virgina, USA\\
% {Digital Forensics - Hardware}  \hfill January 2009 - August 2010

%\begin{itemize} \itemsep -2pt % Reduce space between items
%\item Verified hardware device for nationwide usage
%\item Top pick from University (200 Candidates)
%\end{itemize}
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%	COMMUNITY SERVICE SECTION
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% \section{COMMUNITY \\ SERVICE}
% {\textbf{STEM Volunteering with Kids}}\\
% Volunteering with STEM in Kids is important because it sets up our next generation for success.
%Each one of us has been invested in and its important to invest in our future.
% I served at multiple levels because I wanted to help all kids, not just those who made it to the top.
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% \item Future Cities Competition, {\sl Special Awards Judge} \hfill January 2015 - January 2017
% \item FIRST Robotics, {\sl Robotics and Core Values Judge} \hfill January 2014 - January 2017
%\begin{itemize}  \itemsep -2pt % Reduce space between items
%\item Regional, State, and Local\end{itemize}
%\item FIRST Lego League, {\sl Core Values Judge} \hfill January 2014 - January 2017
%\begin{itemize}  \itemsep -2pt % Reduce space between items
%\item Regional, State, and Local\end{itemize}
% \end{itemize}

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