Mahshid Ahmadian

Ph.D. in Statistics and Data Science.

Data Science & Machine Learning, Statistics, Bayesian methods, spatiotemporal modeling, and making complex quantitative work accessible.

I build predictive models, operationalize complex algorithms, and bridge quantitative science with policy and data-driven decision-making.

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In the News

Mahshid Ahmadian at the Virginia Sea Grant Symposium

American Meteorological Society · June 2026

AMS and Virginia Sea Grant Launch New Policy Fellowship

Selected through a national competitive process to bring statistical modeling and data science expertise to weather, water, and climate decision-making at the AMS Policy Program.

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Summary of Related Skills

Research Methods | Study design, mixed-effects modeling, missing data imputation, reproducible and open-science workflows
Programming | R (Rcpp, Shiny, tidyverse), Python (NumPy, Pandas, scikit-learn), C++, SQL, SAS, SPSS, Git, Jupyter Notebooks
Statistical & ML Methods | Bayesian inference, MCMC algorithms, spatiotemporal modeling, time series forecasting, GLMs, supervised/unsupervised machine learning
AI & LLMs | Prompt engineering, currently exploring agentic workflows for data analysis and research automation
Data Engineering | ETL pipelines, geospatial data (ArcGIS Pro), API integration, REDCap, High-Performance Computing (Slurm)
Data Analysis | Statistical analysis (frequentist and Bayesian), data visualization, Power BI
Communication | Scientific writing, presenting to non-experts, mentorship, team collaboration

Mahshid Ahmadian

AMS and Virginia Sea Grant Launch New Policy Fellowship

Summary of Related Skills

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