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AI/ML @ Wayfair | UVA
I'm a results-oriented Machine Learning leader with a proven track record of building and managing high-performing teams of Machine Learning Engineers and Scientists. My focus is on translating complex business challenges into scalable, data-driven solutions that deliver measurable impact. I'm experienced in leading the full lifecycle of machine learning projects, from ideation and research to deployment and monitoring, with a strong emphasis on building robust and reliable systems. I excel at aligning technical roadmaps with strategic business objectives, fostering a culture of innovation, and empowering teams to leverage cutting-edge technologies to achieve ambitious goals. My background includes successfully delivering projects in areas such as large-scale forecasting, recommendation systems, and data infrastructure development, always prioritizing clear communication and collaboration across technical and non-technical stakeholders.
University of Virginia
Master of Science - MS, Machine Learning
N/A – Present
SVKM's Narsee Monjee Institute of Management Studies (NMIMS)
Master of Science - MS, Biology/Biostatistics
N/A – Present
University of Mumbai
Bachelor of Science - BS
N/A – Present
Wayfair
Senior Machine Learning Manager, Voice of Customer & CX
August 1, 2025 – Present
Hybrid
Wayfair
Senior Machine Learning Manager, Global Forecasting
August 1, 2024 – August 1, 2025
Hybrid
Wayfair
Machine Learning Manager, Global Service Forecasting
March 1, 2022 – July 1, 2024
Hybrid
Red Hat
Senior Data Scientist
March 1, 2021 – March 1, 2022
Red Hat
Data Scientist
July 1, 2018 – March 1, 2021
Peel-works
Data Scientist
September 1, 2015 – May 1, 2017
Millward Brown Vermeer
Research Associate
August 1, 2014 – September 1, 2015
Gurugram, Haryana, India
Indian Institute of Science
Project Trainee
May 1, 2009 – July 1, 2009
Bengaluru, Karnataka, India
Epilepsy Foundation India
April 1, 2013 – May 1, 2014
Music Therapy for Epileptic Children to reduce/control seizure frequency, the possibilities, July 2013 April 2014 Epilepsy – An analysis of 10,000 rural Maharashtra patients An investigation of Speech and language Deficits among children with Epilepsy, with and without cognitive impairment
NMIMS
June 1, 2012 – March 1, 2013
Research projects: ‘A Study of Heavy Metal Pollution (Cadmium) of the Aquatic Environment of Mumbai by Spectrophotometric Method’ under Dr Z.R. Turel, June 2012-March 2013
Cultural Fit Analysis
The candidate has a diverse background, starting with biology/biostatistics and transitioning into data science and machine learning. Their project experience, though older, shows an interest in applying analytical skills to real-world problems. The progression through various data science and ML roles at companies like Red Hat and Wayfair indicates adaptability and a drive for growth. The target role of 'AI Engineer' aligns well with their recent ML management experience and educational background, suggesting a good cultural fit for a technically driven environment.
Soft Skills & Operational Fit
The candidate's experience descriptions suggest strong problem-solving skills and the ability to interface with global leaders, indicating good communication and leadership potential. Experience in managing teams and leading migration projects points to operational effectiveness. However, without specific psychometric test results, a definitive assessment of work attitude, stress handling, and team collaboration is limited.