San Francisco Bay Area, USA
DataKind San Francisco-Bay Area (DataKind SF) launched in August 2014 with the vision of creating examples of successful efforts that bring tech and public good sectors together. In a region well known for attracting top tech talent from around the globe and for its incredible community of data scientists and data enthusiasts, DataKind SF hopes to tap into this community’s desire to have a greater impact both locally and globally. Although the universities, community and culture of the Bay Area have always fostered nonprofits striving for positive change, costs are rising rapidly. Through DataKind, they hope to execute data projects that are often out of reach for organizations that could most greatly benefit from them. With a growing group of core volunteers, DataKind SF is inspired by the opportunity to transform how nonprofits operate by using data more effectively.
Our Team
Abhishek Kapatkar
Abhishek is an engineer with a background in computer science and product development. Currently, he is helping Netflix build its Data Infrastructure and previously helped build a new machine learning infrastructure. He cares deeply about promoting equality, diversity, and social justice. Abhishek joined DataKind because he believes greatly in the potential to harness the power of data science in service of humanity. Outside of work, he enjoys running, traveling, noshing on street food and training for endurance cycling events.
Melinda Tellez
Melinda is a data scientist at Clarify Health in the San Francisco area. She’s worked in a number of areas in healthcare, including, Care Management & Palliative Care, Hospital Quality and Safety, Payment Integrity, and Member and Provider Services, and is passionate about value-based healthcare and cost transparency for all. Before working at a software analytics company, she previously worked as a consultant at one of the largest health insurers in the nation and as a data analyst at Brigham and Women’s Hospital in Boston. She holds a B.S. in Biophysics from UCLA and an M.S. in Computer Information Systems and Data Analytics from Boston University. In her free time, she enjoys traveling with her husband and son, baking, DIY projects and CrossFit.
May 02, 2023
Predicting Well Groundwater Quality Using Cloud-Based Machine Learning: DataKind San Francisco Partners with Aquaya

By DataKind San Francisco Background Access to clean water, sanitation, and hygiene (WASH) is critical for healthy and humane living conditions. Two billion people lack access to safely managed drinking water at home, according to the CDC . Access to safe drinking water and sanitation services can have life or ...

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October 27, 2022
Optimizing Data Pipeline Platforms: DataKind San Francisco Partners with Grameen America

By DataKind San Francisco Background How can data infrastructure be optimized to help support the financial empowerment of women? Currently, only four percent of all small business loans from mainstream financial institutions go to women, according to a report by the National Women's Business Council. As MDRC’s recent impact evaluation ...

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May 16, 2022
Predicting Poverty Using Satellite Imagery: DataKind San Francisco Shares Key Learnings

Background Access to clean water, sanitation, and hygiene (WASH) is critical for healthy and humane living conditions. Clean water and sanitation improves health and supports development in other sectors, such as education (particularly for women and girls), environmental stewardship, and the economy. Policy decisions around development and financing for WASH ...

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May 10, 2022
Understanding Equity in Local Governments: DataKind San Francisco Partners with the City of San José

By DataKind San Francisco How can we better understand equity in local governments and the resources they provide to our communities? The City of San José is the tenth most populous city in the U.S., and one of the most diverse . The City of San José’s Mayor’s Office of ...

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