Presented By O’Reilly and Cloudera
Make Data Work
21–22 May 2018: Training
22–24 May 2018: Tutorials & Conference
London, UK
Maryam Qurashi

Maryam Qurashi
Data Science Consultant, Pivigo

Website

Maryam Qurashi is a data scientist at Pivigo, where she works with data scientists and organizations who are seeking to become more data driven. This means dealing with both the realities and possibilities of how to design and scope a data science project. She’s very interested in and curious about questions of ethics and moral philosophy as applied to data science and technology. Maryam became involved in the data science community in London as an S2DS fellow, following a career in academia as a microscopy image analyst.

Sessions

16:35–17:15 Thursday, 24 May 2018
Predicting rent arrears: Leveraging data science in the public sector
Data science and machine learning, Emerging technologies and case studies
 Location: Capital Suite 10/11 Level: Beginner
Secondary topics:  Financial Services
Jonathan Leslie (Pivigo), Tom Harrison (Hackney Council), Maryam Qurashi (Pivigo)
Average rating: *****
(5.00, 5 ratings)
One major challenge to social housing is determining how best to target interventions when tenants fall behind on rent payments. Jonathan Leslie, Maryam Qurashi, and Tom Harrison discuss a recent project in which a team of data scientist trainees helped Hackney Council devise a more efficient, targeted strategy to detect and prioritize such situations. Read more.