Abhijeet Sugam

• Expertise in building machine learning models and conducting advanced data analysis.
• Extensive experience with Re-designing and migrating the database in RDBMS to a new No-SQL-based database.
• Experienced in collaborating with multifunctional teams to translate system requirements into design specifications

Software Developer – ML Engineer, Import-Export Operations| Amazon India Feb. 2020–Jul. 2022

• Analyzed and guided Development of a robust global trade data engineering platform, streamlining operations for sellers, transporters, and compliance teams, resulting in a significant 27% reduction in duplicate work. • Led end-to-end ownership of projects, from initial analysis to successful implementation, ensuring seamless data flow. • Employed data analysis techniques to optimize cross-border package transit times by an impressive 14.7%. • Applying machine learning algorithms such as regression, classification, and dimensionality reduction to develop predictive models for optimizing import/export processes and forecasting demand. • Leveraging Amazon Web Services (AWS) for storing and processing large-scale trade data using technologies like AWS Glue. • Collaborating with developers and IT teams to deploy machine learning models and data solutions using AWS platforms. • Assessing risks associated with trade operations and applying data-driven approaches to ensure compliance with international trade regulations. • Established and implemented a scalable mechanism for automating root-cause analysis of data issues. The decision trees generated were adopted globally by over 800 associates, spread across 7 worldwide locations.

Software Developer – ML Engineer, Trust and Safety | Google (via CNX) Feb. 2018–Feb. 2020

• Developed data labeling processes from scratch to train machine learning models, improving model accuracy by generating labeled and curated datasets for model training. • Supervised the collecting and analysis of YouTube video consumer data, including categories, views, likes, dislikes etc. • Investigated data to discover trends, patterns, and insights to improve YouTube content management and user experience. • Developed and implemented data visualization techniques, including charts, graphs, and dashboards, to effectively communicate findings to stakeholders and team members. This in turn increased auditor productivity by 10%. • Pioneered data-driven approaches by constructing predictive models capable of categorizing diverse YouTube video types based on their content. • We used CNN on YouTube thumbnail to analyze the basic category of video before Queuing to Content Moderators. • Efficiency Increased by (approx.): Hate speech 60%, SPAM 55%, Graphic Violence 17%, Nudity 22%, Fight 20%, LEWD 30% • Collaborated seamlessly with data scientists, analysts, content managers, stakeholders, aligning data-driven strategies harmoniously with overarching operational goals.

EDUCATION State University of New York at Buffalo (SUNY),

USA Aug 2022 - Dec 2023

Master of Science in Computer Science and Engineering,

3.5 GPA

Courses: Machine Learning, Deep Learning, Computer Vision, Database Management, Algorithm, Blockchain, Information Retrieval, Data Intensive Computing, Stati, Project Management, Predictive Analytics, Statistics

SJB institute of Technology,

India Aug2013-July2017

Bachelor of Engineering in Information Science,

First Class

Courses: Operating System, Software Engineering, Graph Theory, Formal Languages and Automata Theory, File Structures, Discrete Mathematical Structures, Unix shell Programming, Management and Entrepreneurship