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Product-focused technologist @ McKinsey & Co | ex-Nvidia | Data & AI/ML systems
Product-focused technologist with 7+ years of experience building and scaling data and AI/ML systems in highly cross-functional environments. I’ve led development of complex, data-driven products by defining problem scope, aligning technical and product requirements, and collaborating closely with engineers, designers, researchers, and domain experts. Across roles, I’ve worked at the intersection of data science, machine learning, and product execution — from shaping metrics and experimentation strategies to building monitoring systems and accelerating iteration cycles. I enjoy working across disciplines, whether partnering with designers, engineers, 3D artists, or psychometricians, and I’m especially energized by environments where diverse perspectives come together to solve ambiguous problems creatively. I’m deeply interested in building sustainable, inclusive products that balance advanced technology with empathy for user experience. My strength lies in bridging technical depth with product thinking — translating complexity into clear decisions, advocating for the user throughout the product lifecycle, and helping teams focus on what will drive the most impact.
Georgia Institute of Technology
Master of Science (MS), Electrical and Computer Engineering
January 1, 2016 – January 1, 2018
PES University
Bachelor of Engineering (BE), Electrical and Electronics Engineering
January 1, 2012 – January 1, 2016
McKinsey & Company
Data Scientist
December 1, 2020 – Present
Los Angeles Metropolitan Area
Imbellus
AI/ML Engineer
July 1, 2018 – December 1, 2020
Greater Los Angeles Area
Georgia Institute of Technology
Graduate Teaching Assistant
January 1, 2018 – May 1, 2018
Atlanta
NVIDIA
Deep Learning Software Intern
August 1, 2017 – December 1, 2017
Santa Clara, California
Panasonic Automotive
Computer Vision Intern
May 1, 2017 – August 1, 2017
Atlanta, Georgia
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
Coursera
June 24, 2026 – Present
Deep Learning Specialization
Coursera
June 24, 2026 – Present
Sequence Models
Coursera
June 24, 2026 – Present
Deep Learning
DeepLearning.AI
June 24, 2026 – Present
Generative AI Leader
Google Cloud
June 24, 2026 – Present
Convolutional Neural Networks
Coursera
June 24, 2026 – Present
Neural Networks and Deep Learning
Coursera
June 24, 2026 – Present
Structuring Machine Learning Projects
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a strong background in AI/ML and Data Science, working in innovative environments focused on data-driven assessments. This indicates a fit for roles requiring analytical rigor and a proactive approach to problem-solving. However, the target role is 'Data Analyst', which might be a slight pivot from their primary AI/ML engineering and data scientist roles. While the analytical skills are transferable, the specific focus on business intelligence, reporting, and stakeholder communication typical of a Data Analyst role is not explicitly detailed in their experience descriptions. The breadth of projects is focused on AI/ML applications rather than diverse data analysis domains.
Soft Skills & Operational Fit
The candidate's experience at McKinsey & Company and Imbellus, working in cross-functional teams on complex, data-driven products, suggests strong collaboration and problem-solving skills. The focus on 'transforming the measurement of human potential' and 'measuring how people think' indicates an analytical mindset and an ability to tackle abstract problems. However, specific details on communication, leadership, or project management within these roles are not explicitly provided.