boada-cv.tex

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\begin{document}

\name{{\huge\bf Steven Boada, Ph.D}\vspace*{.1in}}

\begin{resume}
\vspace*{-2mm}
\section{Basic\\Information}
\begin{tabular}{@{}p{4.9in}p{4in}}
  (615) 200-0119 & \href{https://github.com/boada}{github.com/boada} \\
  \href{mailto:stevenboada@gmail.com}{stevenboada@gmail.com} & \href{https://linkedin.com/in/theboada}{linkedin.com/in/theboada} \\
\end{tabular}

% \vspace{-3mm}
% Collaborative, scientific thinker passionate about discovering and communicating nuanced insight from complicated data. Background includes: open-source contributions, project leadership, computer vision, traditional machine learning, and working with large, heterogeneous, often noisy datasets.
% \vspace*{-2mm}

\section{Professional \newline Experience}
\textbf{Activision Publishing, Inc.} \hfill Boulder, Colorado\newline
\textit{Lead Data Scientist, Gameplay} \hfill \textbf{March, 2026 - Present}\newline
As part of the game science team, I lead data scientists working to make Call of Duty better for our players. I combine a deep ML engineering background with hands-on people leadership, experimentation strategy, and cross-functional partnerships. Specifically, I:
    \begin{list2}
        \item Define and lead high-impact analytics initiatives with design leadership, analyzing how gameplay systems (maps, modes, weapons, communication systems, etc.) influence player behavior and top-line KPIs, and translating insights into actionable design recommendations.
        \item Own experimentation strategy for gameplay features, guiding the design and evaluation of A/B tests, statistical models, and large-scale player behavior analyses.
        \item Champion gameplay measurement strategy and data quality, partnering with engineering to improve telemetry coverage, instrumentation, and analytical reliability.
        \item Elevate team analytical capability by mentoring data scientists, reviewing experimental designs and analyses, and promoting best practices in experimentation, statistics, and data storytelling.
    \end{list2}
\textit{Senior Data Scientist, Gameplay} \hfill \textbf{January, 2024 - 2026}\newline
    \begin{list2}
        \vspace*{-5mm}
        \item  Restarted advanced gameplay analytics support for partner studios and live Call of Duty titles.
        \item Highlighted Project: Led study design and analysis of input advantage across controller and mouse/keyboard players, directly resulting in a rework of the aim assist system shipped in Black Ops 7 (2025).
    \end{list2}
    \vspace*{-2mm}
\textit{Senior Machine Learning Engineer} \hfill \textbf{January, 2021 - 2024}\newline
    \begin{list2}
        \vspace*{-5mm}
        \item Provided technical direction and leadership to junior data scientists end-to-end — designing, developing, and deploying recommendation systems integrated into Modern Warfare 2 (2022) and Modern Warfare 3 (2023).
        \item Designed and maintained ML infrastructure including autoML, CI/CD pipelines (Jenkins, GitHub Actions), model tracking (MLflow), and orchestration (Airflow).
        \item Developed near-realtime applications (via Spark streaming) to identify and mitigate in-game cheating and malicious behaviors, achieving action times in the low 10s of seconds.
        \item Spearheaded the transition of ML infrastructure from AWS to GCP/GCS, optimizing scalability and performance.
        \item Built customer conversion, churn prediction, and behavioral segmentation models using survival analysis, clustering, and tree-based methods.    
    \end{list2}
\vspace*{-2mm}
\textbf{Insight Data Science} \hfill New York, New York\newline
\textit{Fellow} \hfill \textbf{January, 2020 - 2021}\newline
    \begin{list2}
    	\vspace*{-5mm}
        \item Completed a data science bootcamp focused on transitioning academics into the tech industry, working on real-world data problems.
        \item Built a random forest model in Python to prioritize NYC restaurant inspections, improving violation detection by 2.5\% and identifying critical issues up to 7 days earlier through an AWS-deployed API.
    \end{list2}
\vspace*{-2mm}

% \textbf{Dept. of Physics and Astronomy, Rutgers University} \hfill New Brunswick, New Jersey\newline
% \textit{Postdoctoral Research Associate} \hfill \textbf{September, 2016 - 2021}\newline
%     \begin{list2}
%     \vspace*{-5mm}
%         \item Designed and built parallelized data processing pipelines to analyze TBs of astronomical imaging data, producing standardized catalogs and rigorous results that contributed to 2 peer-reviewed publications and several hundred hours of telescope time.
%         \item Contributed to open-source Python projects focused on astronomy, adding features and fixing bugs in tools like \href{https://github.com/boada/photometrypipeline}{photometrypipeline}, \href{http://astlib.sourceforge.net/}{astLib}, and \href{https://github.com/boada/easyGalaxy}{easyGalaxy}.
%     \end{list2}
%     \vspace*{-2mm}

% \textbf{Dept. of Physics and Astronomy, Texas A\&M University} \hfill College Station, Texas\newline
% \textit{Ph.D Candidate} \hfill \textbf{August, 2010 - 2016}\newline
%     \begin{list2}
%     	\vspace*{-5mm}
%       \item Demonstrated that measurements from a planned large observation campaign could be improved by up to a factor of 3 over traditional statistical methods through the use of machine learning.
%       \item Implemented these machine learning methods and produced reliable results in a pilot survey of the real sky and under real-world conditions.
%     	% \item Collaborated with group members both in person, and through collaborative tools (e.g., GitHub, SVN).
%     	% \item Presented scientific results in high-impact, astrophysical journals and at international conferences.
%     \end{list2}
% \vspace*{-2mm}

% \textbf{The University of Tennessee}, Knoxville, Tennessee USA\newline
% \textit{Master's Candidate} \hfill \textbf{August, 2007 - 2009}\newline
%     \begin{list2}
%     	\vspace*{-5mm}
%       \item Implemented a C-based pipeline to process hundreds of GBs of simulation results. Including a computer vision algorithm to automatically analyze and compare results to expected targets.
%       \item Optimized simulation parameters using a genetic algorithm based search utilizing HPC (100k+ core) systems at the National Center for Computational Science, part of Oak Ridge National Laboratory
%     \end{list2}
% \vspace*{-3mm}

% \section{Awesome Projects}
% \textbf{Using Imaging to Infer Galaxy Properties}\newline
%     \begin{list2}
%     	\vspace*{-5mm}
%       \item Predicted galaxy chemical composition with $\sim$5\% error from pseudo-three color imaging, a result better than other current, similar efforts in the literature. Leveraged CNNs to analyze $\sim$150,000 images of galaxies.
%       \item Project start to publication: 4 months (typically $\sim$1.5 years). See: \href{https://github.com/boada/galaxy-cnns}{github.com/boada/galaxy-cnns}.
%     \end{list2}
%     \vspace*{-3mm}

% \textbf{Predicting Tournament Performance in Warmachine}\newline
%     \begin{list2}
%     	\vspace*{-5mm}
%     	\item Created an \href{https://en.wikipedia.org/wiki/Elo_rating_system}{Elo} based model to forecast the results of upcoming tournaments and identify potential upsets.
%     	\item Integrated predictions into a local community ranking system and forecasted $\sim$1800 tournament game results of the popular tabletop game using Python (e.g., Pandas).
%     \end{list2}
% \vspace*{-1mm}

\section{Skills}
\textbf{Machine Learning:} Linear Models, Decision Trees, SVM, Clustering, Deep Learning, Survival Analysis\\
% \textbf{CI/CD:} Jenkins, Airflow, Docker\\
% \textbf{Statistical Methods:} Hypothesis testing, error analysis, Monte Carlo methods, maximum likelihood\\
\textbf{Engineering \& MLOps:} Open Source Contributor, Python, Spark, SQL, MLflow, Airflow, Docker, Jenkins, GitHub Actions, AWS, GCP, Databricks \\
\textbf{Leadership:} Team management, mentorship, experimental design review, cross-functional stakeholder communication, workshop facilitation, Eagle Scout\\
\textbf{AI \& Agentic Systems:} LLM integration (Claude, GPT), prompt engineering, agentic workflow design, multi-agent orchestration, AI coding tools (Claude Code, GitHub Copilot, etc.)\\
\vspace*{-7mm}

%section for two column education
\section{Education}
\begin{tabular}{@{}p{3in}p{3in}}
  \textbf{Texas A\&M University}, College Station, Texas
  \begin{list2}
  	\item Ph.D, Physics (astronomy focus), 2016
  \end{list2} &
  \textbf{The University of Tennessee}, Knoxville, Tennessee
  \begin{list2}
  	\item M.S., Physics (astronomy focus), 2009
  	\item B.S., Physics, 2007
  \end{list2} \\
\end{tabular}
\vspace*{-4mm}

\end{resume}
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