This project is a collaborative eﬀort with UMBC as the coordinating as well as implementing organization and the University of Baltimore (UB), Towson University, and Bowie State University as implementing organizations. BNIA-JFI will be a part of a team of experts with multidisciplinary academic expertise and complementary training experiences in parallel computing, data science, big data, cybersecurity, virtual reality, geospatial data analysis, and urban and regional planning. BNIA-JFI will support integration of real-world data science projects by 1) recruiting and introducing data science tools and techniques to undergraduate students at UB; 2) accelerating the adoption of advanced data science techniques, such as geospatial analysis for projects in urban communities through community-based real-world projects.
This project has been supported by NSF grant IIS-1923982.
Application Deadline: May 15th, 2021
How to Apply: See eligibility requirements in detailed job description above and then send cover letter and resume to Seema Iyer [email protected] by the deadline.
If you are interested in getting conceptual and hands-on experience in data science and get paid for it, consider applying for the following opportunity. The Baltimore Neighborhood Indicators Alliance (BNIA) at the University of Baltimore is seeking Undergraduate students to be a part of a Baltimore regional Data Science Corps. Students will be trained on data processing best practices for analysis, geographic information systems, effective and ethical data visualization techniques for applications that help communities in Baltimore understand the current impacts of the COVID19 pandemic. The students will work with BNIA staff and faculty mentors and will be involved in real-world projects.
This position will run for three months in the fall of 2020. Students will be introduced to several data science learning opportunities with BNIA staff and other online training in order to work on the projects outlined above. Learning modules and team meetings will be approximately 3-5 hours per week. Time spent on projects will be approximately 8 hours per week.
Our students are going through rigorous training on Data Science techniques that can be used for social good. We are looking for organizations that have a data science question or need that could serve as both a learning opportunity for the students as well as a service to your organization/agency.
If you are interested in hosting a student for a semester, please fill out this Host Intake Form
1) Analyze databases regarding internet speeds by neighborhood
2) Create a web scraper to collect routinely updated data on websites that don’t have an open data API
3) Review real time service of new bus schedules and see if different neighborhoods are
experiencing service disruptions
4) Analyze city budgets for youth related spending and programs
Ruth Robinson – Recycling Cart Rollout ’21
Lalla N’diaye – AI Solar Output In The Baltimore Metropolitan Area
Hannah Boyd – Covid-19 Vaccine Distribution in Baltimore City
Michael Vandi – Understanding the Importance of Data Documentation
Ruth Robinson – Social Media Alert System for COVID-19 Illicit Behavior
Brian Kelly – An Analysis of Baltimore City E-Scooter Distribution
Michael Vandi and Naomi Weiss – GIS with the BNIA Data Science Corp
Ruth Robinson and Priya Kanneboyina – Is Baltimore City Getting Fast Enough Internet Speeds?
Degree: Applied Information Technology/Cybersecurity
Graduation Date: Winter 2021
“I have always wanted a career in the Database Management System, and seeing an opportunity to work with professionals, dealing with real-life data is an avenue for me to get familiar with data and one step closer to my dreams of becoming a Data Analyst. I look forward to working with the group on analyzing data from Baltimore city or other sources, also to discover hidden insight, and to accomplish the project goal.”
Ruth Robinson, Degree: Business Administration – Real Estate and Economic Development Concentration, Graduation Date: Spring 2022
Brian Morrison, Degree: M.S., Applied Industrial & Organizational Psychology, Graduation Date: Spring 2022
Lalla N’diaye, Degree: Business Administration- Accounting, Graduation Date: Spring 2021
Michael Vandi, Degree: Applied Information Technology, Graduation Date: Fall 2020
Brian Kelly, Degree: Upper-Division Certificate in Computer Programming, Graduation Date: Fall 2020
Surafel Beyene, Degree: Applied Information Technology – Application Development & Programming, Graduation Date: Fall 2020
Naomi Weiss, Graduation Date: Fall 2020
Priya Kanneboyina, Degree: Applied Mathematics, Graduation Date: Spring 2023
This project has been supported by NSF grant IIS-1923982