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Director, Amazon Sponsored Products and Brands
I am a senior leader with 18+ years of experience working at the intersection of machine learning, product and engineering, to create products that delights the customers. My experience has more evolved into the advertising domain having significant experience in building, leading, and scaling engineering, product, and ML teams in different realms of the advertising stack including relevance, product development, ad sourcing, bidding, and auctions. Working backwards from the customer problem, and using science and technology as tools to build solutions that addresses these customer needs (and even more), drives me as a technology leader. I build teams and leaders, and create opportunities for all to professionally develop by scoping opportunities for team members to progressive own areas of high complexity, and manage them independently. I take pride in the teams I have built, ensuring diversity & inclusiveness in its core DNA. I find ways to get things done: indexing on durable and programmatic solutions, but not hesitant to invent and simplify when needed. I am driven by curiosity and this has encouraged me to work in disparate domains: legal, hardware devices, crowdsourcing platforms, customer engagement, advertising, and payments. Each of these experiences have cumulatively made me stronger, wiser, and hungrier for more challenges. My range of experience spans between defining business metrics to developing and implementing ML-driven solutions that scale real-time. Technical specialties: Data science, machine learning, econometrics, statistics, data mining, advertising, business intelligence, data analytics.
Udacity
Deep Learning Nanodegree, Deep Learning
September 1, 2020 – January 1, 2021
University of Washington
Certificate in Machine Learning, Machine Learning
January 1, 2015 – January 1, 2015
UC San Diego
Certification in Data Mining, Data Mining, Machine learning
January 1, 2013 – January 1, 2014
Texas A&M University
Doctor of Philosophy (PhD), Econometrics and Industrial Organization
January 1, 2001 – January 1, 2007
Jawaharlal Nehru Technological University
Master of Arts (M.A.), Economics
January 1, 1998 – January 1, 2000
St. Xavier's College
Bachelor of Science (BSc), Economics
January 1, 1995 – January 1, 1998
Amazon
Director, Amazon Sponsored Products and Brands
January 1, 2026 – Present
Seattle, Washington, United States · On-site
Indeed
Sr. Director of AI and Engineering
June 1, 2024 – December 1, 2025
Seattle, Washington, United States · On-site
Amazon
Machine Learning and Product Head, Amazon Sponsored Products
February 1, 2021 – June 1, 2024
Seattle, Washington, United States
Microsoft
Principal Applied Science Manager (Sr. Director)
December 1, 2019 – February 1, 2021
Greater Seattle Area
Amazon
Global Head of Machine Learning - Amazon Payments
June 1, 2019 – December 1, 2019
Northeastern University
Adjunct Faculty
January 1, 2019 – December 1, 2024
Seattle, Washington, United States
Amazon
Senior Manager - Machine Learning, Amazon Sponsored Ads
October 1, 2017 – May 1, 2019
Amazon
Senior Manager Research Science, Consumer Engagement
April 1, 2017 – October 1, 2017
Amazon
Manager - Research Science, Consumer Engagement
April 1, 2015 – March 1, 2017
Amazon
Sr. Research Scientist
July 1, 2013 – April 1, 2015
Amazon
Sr Data Scientist
June 1, 2012 – July 1, 2013
ARPC
Director
May 1, 2011 – June 1, 2012
Washington DC-Baltimore Area
Digonex Technologies
Director of Analytics
August 1, 2010 – May 1, 2011
Analysis Group
Associate
October 1, 2007 – August 1, 2010
Texas A&M University
Graduate Teaching Assistant
August 1, 2002 – August 1, 2007
Generative AI
Udacity
June 24, 2026 – Present
Generative AI with Large Language Models
DeepLearning.AI
June 24, 2026 – Present
Natural Language Processing Specialization
Coursera
June 24, 2026 – Present
Natural Language Processing with Sequence Models
Coursera
June 24, 2026 – Present
Natural Language Processing with Probabilistic Models
Coursera
June 24, 2026 – Present
Natural Language Processing with Classification and Vector Spaces
Coursera Course Certificates
June 24, 2026 – Present
Deep Learning Specialization
Coursera
June 24, 2026 – Present
Introduction to Big Data Analytics (2015)
Coursera Course Certificates
June 24, 2026 – Present
Introduction to Big Data
Coursera Course Certificates
June 24, 2026 – Present
Programming for Everybody (Python)
Coursera Course Certificates
June 24, 2026 – Present
AI Agents with LangChain and LangGraph
Udacity
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's career path demonstrates a strong fit for a data-driven, innovative, and fast-paced environment, typical of large tech companies. Their experience across various domains within AI/ML (advertising, payments, marketplace optimization, consumer engagement) shows adaptability and a broad interest in applying data science to complex business problems. The academic background and continuous learning through certifications (Generative AI, Deep Learning, NLP) indicate a commitment to staying current with emerging technologies. The target role of 'Data Analyst' seems significantly junior to their demonstrated experience and leadership capabilities, suggesting a potential mismatch in role expectations or a strategic career shift not fully explained by the resume.
Soft Skills & Operational Fit
The candidate's extensive leadership roles at top-tier companies like Amazon, Indeed, and Microsoft suggest strong operational leadership, strategic thinking, and the ability to manage large, diverse technical teams. Their experience in scaling programs and driving innovation indicates a proactive and results-oriented approach. The adjunct faculty role also points to strong communication and mentorship skills. While no psychometric test results are available, the career trajectory implies high logical reasoning and stress handling capabilities.