Data Scientist

Brennan Hall

**************@*****.*** 408-***-**** San Jose, California

linkedin.com/in/brennan-hall789 github.com/brennanhall789 Summary

Results-oriented Statistician and Data Scientist with an MA in Mathematical Statistics and 7+ years of experience solving complex business challenges through statistical analysis. Expert in statistical inference, experimental design, sampling theory, and translating data analytics into actionable business strategies. Proven track record of driving data-informed decision making using R, Python, and advanced statistical methods across public and private sectors. Skilled at turning complex statistical models into clear, actionable insights that drive measurable outcomes in workforce optimization, financial forecasting, and survey analytics. Experience

Customer Value Partners, Statistician December 2023 -– April 2025

• Consultant to the Office of the Chief Human Capital Officer (OCHCO) at the Dept. of Homeland Security.

• Designed and implemented predictive attrition models that identified key factors driving voluntary departures to guide development of new recruitment and hiring practices.

• Developed time series regression models incorporating forecasts that improved workforce planning accuracy.

• Spearheaded a data governance initiative that streamlined data product development and standardized metrics across OCHCO teams.

• Collaborated cross-functionally with Finance and HR to create forecasting models that optimized hiring budgets and personnel planning and capacity across the agency.

• Generated comprehensive workforce capacity reports that directly influenced executive decisions on hiring priorities, ensuring capacity directives were met. US Census Bureau, Statistician September 2021 – November 2023

• Lead researcher on analysis of experiment to discover efficacy and impact of robocall strategies on survey response rate compared to traditional telephone follow-up calls, utilizing survival analysis techniques.

• Led statistical research supporting the Economic Census programs, investigating ways of improving data quality for national and regional economic indicators.

• Specified, tested, and implemented processes to review imputation, estimation, and disclosure requirements for economic surveys per federal regulations.

• Executed maintenance routines for economic survey data during collection periods, verifying data quality and integrity throughout the survey life cycle.

Hull Tactical Asset Allocation, R Developer March 2020 – April 2020

• Consulting project to test an intraday (minutely) trading strategy of \ES futures in comparison to other strategies by constructing a simulator of the strategy.

• Findings validated trading strategies and informed quantitative research initiatives. Cisco Systems, Strategic Programs Systems Analyst January 2015 – August 2016

• Owner of Cisco’s Analytics Incubation Center responsible for strategic planning and testing of new and promising analytic technologies.

• Business development technical lead for initiative on predictive meta data and predictive tools for the digital supply chain.

Projects

Robocall Efficacy Survey Analysis GitHub Repository (Robocalls)

• Conducted survey experiment to investigate the efficacy of robocalls on survey response rates for the US Census Bureau’s Service Annual Survey.

• Established survey parameters, experimental design and hypotheses, and coordinated data requirements for analysis.

• Performed analysis of survey results using Cox Proportional Hazards Regression model, identifying a non-significant difference in survey response rates between robocall and and traditional telephone follow-up contact strategies.

Exact Sampling of Affine Stochastic Processes GitHub Repository (Exact Sampling)

• Developed novel sampling methodology for affine-jump processes under exponential change of measure, enabling unbiased estimates of small probability events.

• Successfully implemented bias correction techniques for high-dimensional processes, achieving an exact sampling algorithm.

• Presented findings at the SIAM Conference for Financial Mathematics (2019), receiving recognition for an innovative approach to time-dependent drift coefficient challenges. Financial Market Volatility Prediction GitHub Repository (NFLX Prediction)

• Implemented ARIMA-GARCH models to capture and forecast stochastic volatility in financial time series. Medical Injury Factor Analysis GitHub Repository (TBI Classification)

• Conducted analytical investigation into the factors contributing to the likelihood of traumatic brain injuries among collegiate athletes using Classification and Principal Component Analysis. Technical Skills

Programming & Tools: R (tidyverse, caret, forecast), Python (scikit-learn, pandas, numpy), SAS, SQL Statistical Methods: Predictive Modeling, Regression Analysis, Survival Analysis, Time Series Analysis, Experimental Design, Monte Carlo Simulations, Sampling Theory Machine Learning: Classification, Clustering, Dimensionality Reduction, Model Validation, Feature Engineering

Data Visualization: ggplot2, PowerBI, Executive Reporting Education

University of California, Santa Barbara September 2016 – September 2019 MA in Mathematical Statistics

• Graduate Teaching Assistant: Stochastic Processes, Time Series Analysis, Regression Analysis, Probability Theory, Introduction to Mathematical Finance Loyola Marymount University, Los Angeles, CA August 2011 – December, 2014 BS in Applied Mathematics

BS in Economics

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