I am very interested to apply for the position of Volunteer at the Solve for Good platform.I am a second-year graduate student pursuing an MS in Environmental Science and Policy at the Harris School of Public Policy (University of Chicago) and I will be graduating in December 2020 only. I am currently involved in a climate science emulator research project and spatial data analysis for modeling air quality along the Chicago bus routes. I have gained skills in data analysis and worked on Big Data during my 2 year course here at the school. I am proficient with the use of statistical tools such as Python, R, STATA, SQL, NoSQL-MongoDB, Neo4j, Q-GIS, and MS Excel and have worked with big datasets. Along with quantitative skills, I have completed a Qualitative Analysis course at the University and I am proficient with MAXQDA software. I have built my skills in data visualization using R, Python, Tableau & Looker. I have completed projects in predictive analysis and have built a ETL pipeline to estimate the energy efficiency of the buildings in Chicago. I worked as a consultant to government projects in India for more than 5 years and was involved systems development and business functional consulting roles. I also had worked in techno-commercial consulting for off-shore projects and have project management experience of a thermal power plant and manufacturing industry. I am interested in data analysis and engaging insightful predictive analysis which creates value propositions and solutions for the organization.

Personal information
Full name: Bibind Vasu
User name: bibindvasu
Organization memberships
Not a member of any organization.
Awards
First 1000 volunteers
Volunteer background
Education: Bachelor's on MS in Environmental Science and Public Policy (University of Chicago)
LinkedIn profile
Github profile
Volunteer availability
Start date: June 20, 2020
End date: None
Hours available per week: 10
Volunteering interests
No stated preferences.
Skills
Skill
Beginner
Intermediate
Expert
Python
GIS tools
Text Data (NLP)
Geospatial
Data in Text Files
Data > 1TB
Network/Graph Data
Multimedia Data (Video or Audio)
Data from Sensors
SQL
Data in Relational Databases
Experience working on real-world problems using data
Social Science (Economics, Sociology, etc.)
Data Visualization
Experimental Methods (RCTs, A/B testing, etc.)
Data Analysis
Causal inference
Decision Trees
SVMs
Random Forests
Neural Networks / Deep Learning
Time Series Models
Unsupervised models
Semi-Supervised models
Graphical models
Regression Discontinuity
Instrumental Variables
Matching (e.g., Propensity Score Matching )
R
Stata
SPSS
SAS

Volunteer projects

No volunteer work yet.