Harshala Jambhulkar works in monitoring and evaluation (M&E) at the United Nations Development Programme (UNDP), where she designs and implements the M&E strategy for a climate resilience project. Her work includes collecting and analyzing ecosystem-based data on adaptation, ecosystem restoration, and climate-adaptive livelihoods.

What did you do before joining this program and what do you do now?

I was part of AshokaX’s Professional and Executive Development Program (PEDP) in Data Science for Social Impact from September 2024 to April 2025. I am working on monitoring and evaluation at UNDP for a project titled ‘Enhancing Climate Resilience of India’s Communities’ in association with the Ministry of Environment, Forest and Climate Change and the Government of Maharashtra. My work involves developing a monitoring and evaluation strategy for ecosystem-based adaptation approaches to restoration and climate-adaptive livelihood activities. It consists of data monitoring for physical, ecological, and socio-economic vulnerability parameters and project activities to inform decision-making, identify priority areas for adaptation planning, and recommend interventions to strengthen institutional capacity for on-the-ground implementation.

How has your approach and work evolved based on what you have learned and observed from your colleagues across the CAN network? How are you applying your newly acquired skills in your work?

During PEDP coursework, engaging with professors and experts through peer learning and collaborative sessions, I have learned innovative ways of integrating data science for climate and other related projects. This significantly shaped my approach to adopt more holistic and evidence-driven use cases in monitoring and evaluation work. One key progression in my practice has been the application of advanced data analytics and visualization techniques to better track parameters and project outcomes by making reporting insightful and actionable for stakeholders. One of the primary concerns while collaborating with community-level interventions is the availability of landscape- or sub-district-level datasets combining physical, social, and economic parameters. I am also leveraging the practice of co-creating monitoring frameworks, using predictive analytics to identify emerging areas of intervention, with the use of administrative and secondary data to prioritize adaptation interventions more effectively. The culture of continuous learning and collaborative ethos at PEDP and CAN network encouraged my learning experience to design adaptive and data-driven solutions at the intersection of climate and health interventions. 

What motivated you to join this program within CAN? How do you intend to stay connected with your peers and the wider CAN community?

My motivation to join the AshokaX PEDP within the CAN network stemmed from a desire to deepen my expertise in applying data science to address complex challenges at the intersection of climate and social impact. Recognizing the growing importance of evidence-driven decision-making, I sought to learn from leading academics, practitioners, and peers who are leading innovative approaches and data science applications for practical and impact-oriented interventions. To stay connected with peers and the wider CAN community, I am keen to contribute by sharing insights and learning from other experiences via online alumni platforms, webinars, and collaborative projects to remain at the forefront of emerging practices.

How was CAN’s interdisciplinary approach to data training helpful in driving impact in your work? How do you measure success?

CAN’s PEDP program’s interdisciplinary approach combines perspectives from foundational math and statistics, climate and health science, the latest tools and methods in data science, and policies and data analytics. The program’s combination of lecture sessions with peer discussions, application-oriented assignments, and a capstone project provides an integrated exposure to collaborative and interdisciplinary problem-solving. I believe the extent to which data-driven insights can lead to tangible changes on the ground is the measure of success. It is reflected in increased resilience of vulnerable communities, dynamic institutional capability for climate adaptation, and integration of monitoring and evaluation frameworks in policy and practice across partners and stakeholders. 

What advice do you have for data and AI practitioners as they begin purpose-driven careers? Why should they apply their skills in the social impact sector?

Embracing the interconnected nature of work in the social impact sector is key to understanding complex dynamics and deep local context for implementation on the ground. There is a growing need for data and AI practitioners’ technical skills in this space, which can be combined with interdisciplinary, data-driven solutions to ensure equitable and context-specific interventions, optimize resource allocation, and measure real-world changes for dynamic feedback. The integration of systems thinking with stakeholder engagement while working in the impact sector allows one to be part of co-creation, collective progress, and convergence for horizontal and vertical integration to build institutional capacity to make a difference.