Hello, I'm Matthew Dannenberg, a mathematician and data scientist with a Ph.D. in Mathematics and several years of experience teaching, modeling complex systems, and building data pipelines. I have strong technical skills in Python (Pandas, Scikit-learn, NumPy, SciPy, Statsmodels), PostgreSQL, and AWS, along with expertise in statistical analysis, geospatial data, and machine learning. My recent work includes building end-to-end analytical workflows and predictive models for environmental and climate-related datasets. I'm motivated to volunteer because I want to use my technical skills to directly benefit communities and address pressing social challenges. After years in academia, I'm eager to apply rigorous analysis to real-world problems where the impact is tangible and measurable. I'm particularly interested in projects involving environmental data, public health, resource allocation, or civic systems. I work well in collaborative settings, value clear communication, and enjoy translating technical findings into actionable insights for diverse stakeholders. I'm flexible on time commitment and open to both short-term analytical projects and longer-term initiatives where I can contribute meaningfully. My goal is to build a portfolio of impactful work while learning from experienced practitioners and contributing to projects that make a genuine difference. Best, Matthew Dannenberg

Personal information
Full name: Matthew Dannenberg
User name: matthewdannenberg
Organization memberships
Not a member of any organization.
Awards
No awards received yet.
Volunteer background
Education: PhD on Mathematics (Stony Brook University)
LinkedIn profile
Volunteer availability
Start date: Jan. 28, 2026
End date: None
Hours available per week: 8
Volunteering interests
No stated preferences.
Skills
Skill
Beginner
Intermediate
Expert
Computer Science (Algorithms)
Python
Java
Network/Graph Data
Geospatial
SQL
Data in Relational Databases
Data from Sensors
Multimedia Data (Video or Audio)
Text Data (NLP)
Data in Text Files
Data > 1TB
Data Visualization
Experimental Methods (RCTs, A/B testing, etc.)
Experience working on real-world problems using data
Data Analysis
SVMs
Random Forests
Neural Networks / Deep Learning
Time Series Models
Unsupervised models
Semi-Supervised models
Graphical models
Decision Trees
Causal inference
Matlab
Julia
R

Volunteer projects

No volunteer work yet.