BARI SARA GROSSMAN
Baltimore
Summary
Doctorally trained Statistician and Data Scientist with advanced expertise in statistical methodology, computational modeling, and applied data analysis. Combines deep theoretical knowledge in epidemiology and public health with extensive practical experience in developing statistical software, implementing machine learning algorithms, and designing robust analytical pipelines. Proven ability to translate complex research questions into rigorous statistical frameworks and deliver actionable insights across diverse domains.
Overview
9
9
years of professional experience
1
1
Certification
Work History
Statistician / Computational Epidemiologist
Johns Hopkins Bloomberg School of Public Health
Baltimore, MD
01.2024 - Current
- Designed and implemented complex statistical models (including GLMMs and survival models) to analyze longitudinal health outcomes in urban populations
- Developed Bayesian hierarchical models to account for spatial and temporal dependencies in disease transmission data
- Created simulation frameworks for statistical power analysis and study design optimization for multi center trials
- Led methodological development for handling missing data and selection bias in observational health databases
- Mentored graduate students in statistical methodology and computational implementation
Doctoral Research Fellow - Statistical Methodology
Johns Hopkins University
Baltimore, MD
01.2019 - 01.2024
- Developed and validated novel statistical methods for causal inference in complex observational studies
- Created comprehensive R packages implementing specialized statistical techniques for epidemiological research
- Implemented parallel computing algorithms to enable computationally intensive bootstrapping and permutation tests
- Designed statistical approaches for integrating multiple data sources with differing measurement structures
- Published methodological innovations in peer-reviewed statistical and bioinformatics journals
Graduate Research Assistant - Statistical Analysis
UCLA Fielding School of Public Health
Los Angeles, CA
01.2017 - 01.2019
- Conducted statistical analysis for health policy evaluations using difference-in-differences and interrupted time series designs
- Developed statistical quality control systems with automated anomaly detection for large scale health datasets
- Implemented propensity score matching and weighting methods to address confounding in program evaluations
- Created standardized statistical reporting templates for research consortium publications
Education
Doctor of Philosophy (PhD) - Public Health (Epidemiology & Population Health)
Johns Hopkins Bloomberg School of Public Health
Baltimore, MD01.2024
Master of Public Health (MPH) - Health Policy & Management
UCLA Fielding School of Public Health
Los Angeles, CA01.2019
Bachelor of Science (BSc) - Health Sciences (Pre-Medicine)
University of Michigan
Ann Arbor, MI01.2017
Skills
- Statistical Methodology
- Advanced Modeling
- Bayesian Statistics
- Generalized Linear Mixed Models (GLMM)
- Survival Analysis
- Cox PH
- AFT
- Time Series Analysis
- Spatial Statistics
- Causal Inference
- Propensity Scores
- IV
- Experimental Design
- RCTs
- Observational Studies
- Quasi-Experimental Designs
- Power Analysis
- Sample Size Calculation
- Machine Learning
- Supervised
- Regression
- Classification
- Ensemble Methods
- Unsupervised
- Clustering
- PCA
- Dimensionality Reduction
- Model Validation & Selection
- Multivariate Analysis
- Factor Analysis
- Structural Equation Modeling
- Multilevel/Hierarchical Modeling
- Computational Statistics
- Statistical Programming
- R
- Tidyverse
- Shiny
- Ggplot2
- Caret
- Lme4
- Rstan
- Survival
- Python
- Statsmodels
- Scikit-learn
- PyMC3
- Lifelines
- Data Processing
- SQL
- PostgreSQL
- Data Wrangling
- Pandas
- Dplyr
- Big Data Techniques
- Visualization
- Matplotlib
- Plotly
- D3js
- Dashboard Development
- Reproducible Research
- R Markdown
- Jupyter Notebooks
- LaTeX
- Version Control
- Git
- Research Software & Infrastructure
- High-Performance Computing
- Parallel Processing
- Algorithm Development
- Statistical Software Package Development
- API Development
- Cloud Computing
- AWS
- Containerization
- Docker
Certification
- AWS Certified Cloud Practitioner
- Advanced Statistical Modeling with R (Coursera)
- Bayesian Statistics Specialization (University of California, Santa Cruz)
- Causal Inference in Data Science (edX)
Affiliations
- American Statistical Association (ASA)
- International Biometric Society (IBS)
- Royal Statistical Society (RSS)
- Association for Computing Machinery (ACM) - Special Interest Group on Statistics
Custom Section
Advanced Modeling: Bayesian Statistics, Generalized Linear Mixed Models (GLMM), Survival Analysis (Cox PH, AFT), Time Series Analysis, Spatial Statistics, Causal Inference (Propensity Scores, IV), Experimental Design: RCTs, Observational Studies, Quasi-Experimental Designs, Power Analysis, Sample Size Calculation, Machine Learning: Supervised (Regression, Classification, Ensemble Methods), Unsupervised (Clustering, PCA, Dimensionality Reduction), Model Validation & Selection, Multivariate Analysis: Factor Analysis, Structural Equation Modeling, Multilevel/Hierarchical Modeling, Statistical Programming: R (tidyverse, shiny, ggplot2, caret, lme4, rstan, survival), Python (statsmodels, scikit-learn, PyMC3, lifelines), Data Processing: SQL, PostgreSQL, Data Wrangling with pandas/dplyr, Big Data Techniques, Visualization: ggplot2, Matplotlib, Plotly, D3.js, Dashboard Development, Reproducible Research: R Markdown, Jupyter Notebooks, LaTeX, Version Control (Git), High-Performance Computing, Parallel Processing, Algorithm Development, Statistical Software Package Development, API Development, Cloud Computing (AWS), Containerization (Docker)
References
Available upon request
Timeline
Statistician / Computational Epidemiologist
Johns Hopkins Bloomberg School of Public Health
01.2024 - Current
Doctoral Research Fellow - Statistical Methodology
Johns Hopkins University
01.2019 - 01.2024
Graduate Research Assistant - Statistical Analysis
UCLA Fielding School of Public Health
01.2017 - 01.2019
Doctor of Philosophy (PhD) - Public Health (Epidemiology & Population Health)
Johns Hopkins Bloomberg School of Public Health
Master of Public Health (MPH) - Health Policy & Management
UCLA Fielding School of Public Health
Bachelor of Science (BSc) - Health Sciences (Pre-Medicine)
University of Michigan