I'm Ridhima, an economist, policy consultant, data-scientist (in making), and aspiring writer-illustrator, living in New Delhi, India.
I have a distinct experience of working and collaborating with academic, governmental, public and private organizations across the globe. Specific examples include McKinsey, New York University, IBM, Barclays, USDA, USPTO, and USAID.
By way of academic training, I have a Masters in Economics from Delhi School of Economics (New Delhi, India, 2012) and a Masters in Public Policy and Management from Heinz College, Carnegie Mellon University (Pennsylvania, United States, 2016).
Between 2017-18, I worked as a Research Scientist with New York University, and researched the economics of disruptive innovation, while also lending management and training support towards a unique training program in evidence-driven decision making. The latter served senior policy professionals in Federal and State governments, and was later adopted for a graduate level class in New York University.
In 2020, I'm working on a range of policy initiatives. For more information, you can jump to the end of this page.
Selected Work Experiences
McKinsey Global Institute, McKinsey and Company
Advisor, Economics and Data Science
Associate Research Scientist
New York University
Centre for Urban Studies+Progress, Wagner School of Public Policy
Research & Analytics, IBM
April 2019- present
Jan 2017 - present
May 2017-Dec 2018
Feb 2013-July 2015
May 2012-July 2013
Selected Teaching & Workshops
Core Team, Coleridge Initiative, New York University
(joint collaboration with University of Chicago & University of Maryland)
Core Faculty, Econometric Modeling and Artificial Intelligence Workshops
(an Infinite Sum Modeling initiative)
sponsored by: National Institute of Micro, Small and Enterprises, India
All India Management Association, India
- Regression Analysis
- Discrete Choice Modeling (Logistic + Probit)
- Data Manipulation
- ReGex (Record Linkage + Text Mining)
- Machine Learning Methods
- R Studio, Python
- Excel VBA
Publications and Conferences
(Author) “ Global Spending on Family Planning and Reproductive Health, 2018 ” (Journal, Center for International Relations and Politics, Institute of Politics and Strategy, Carnegie Mellon University)
(Author) “ Money for Something: The Links between Research Funding and Innovation ” (IZA, 2018)
(Research Support) “ Family Planning in the Context of Latin America's Universal Health Coverage Agenda ” (Global Health: Science & Practice)
(Research Support) “ Can differentiated care models solve the crisis in HIV treatment financing? Analysis of prospects for 38 countries in sub-Saharan Africa ” (Global Health: Science & Practice)
(Author) “ Smart Street Sweeping in the City of Pittsburgh, PA” (Panel Paper, APPAM, Washington DC, 2017)
Tools: R-Studio, Python, STATA, GAMS, SAS (Windows, Enterprise Guide, Miner), SQL, Office (Excel, VBA), ArcGIS
Methods: Regression Analysis, Machine Learning Methods, Impact Evaluation, Topic Modeling, Spatial Analysis, Visualization, Regular Expressions (RegEx), Econometric Modeling
Thanks for visiting my page!
I'm presently engaged with McKinsey's Global Institute (MGI). My current project involves researching the effect of technology on economic growth and labor force planning across the globe. You can read about McKinsey's work in this space here.
I also work with, and represent Infinite Sum Modeling, a boutique consulting firm with a global clientele of Harvard Medical School, World Bank, Asian Development Bank, UNCTAD, and many others. Should you require our expertise, please reach out.
An academic at heart, I routinely take curated data science training/workshops for graduate students and employees at major public and private organizations.
Pro Bono Interests: I volunteer my time for research and fundraising for a small NGO working primarily in the field of education, in Bhadhoi, Uttar Pradesh, India. In the last 3 years, FARF has sponsored the education of over 200 kids, without any external funding. I will be grateful if you can donate for this noble cause. Link here.
For consultative assignments, please drop me a note through the contact page, or at email@example.com. I will be happy to help you as my time and skill permits.
Disclaimer: This website is purely my own work, and in no way, represents the opinions, research, or consultative work done by me, or my co-workers, friends, and acquaintances at McKinsey and Company and its affiliate institutions.