Iman Haji

Master of Science in Engineering

Sept 2021 - June 2022

University of Washington | Seattle, WA

Dean's List

Bachelor of Science in Engineering

Sept 2018 - June 2021

University of Washington | Seattle, WA

Dean's List

Software Engineer

Sept 2022 - Present

Amazon | Seattle, WA

• Contributed to the launch of a high-visibility customer-facing streaming product serving over 5 million customers that seamlessly aggregates content from over 400 providers, enabling users to stream live channels and on-demand videos spanning multiple genres.
• Led the end-to-end implementation of on-demand video and live channel metadata caching, significantly reducing content latency by 70% and ensuring a seamless and responsive streaming experience.
• Architected and executed two essential APIs facilitating seamless data integration and communication between backend metadata workflow and the front-end client, ensuring real-time content updates and data consistency.
• Directed the operational readiness and optimization of engagement services and infrastructure, empowering the app to track engagement metrics effectively; optimized the AWS Redshift cluster for improved data ingestion and analytics.
• Designed and implemented features enabling users to favorite categories as a precedent for personalized content recommendations, resulting in increased user engagement and streamed hours.

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Master of Science in Engineering

Sept 2021 - June 2022

University of Washington | Seattle, WA

Dean's List

Bachelor of Science in Engineering

Sept 2018 - June 2021

University of Washington | Seattle, WA

Dean's List

Software Engineer

Sept 2022 - Present

Amazon | Seattle, WA

• Contributed to the launch of a high-visibility customer-facing streaming product serving over 5 million customers that seamlessly aggregates content from over 400 providers, enabling users to stream live channels and on-demand videos spanning multiple genres.
• Led the end-to-end implementation of on-demand video and live channel metadata caching, significantly reducing content latency by 70% and ensuring a seamless and responsive streaming experience.
• Architected and executed two essential APIs facilitating seamless data integration and communication between backend metadata workflow and the front-end client, ensuring real-time content updates and data consistency.
• Directed the operational readiness and optimization of engagement services and infrastructure, empowering the app to track engagement metrics effectively; optimized the AWS Redshift cluster for improved data ingestion and analytics.
• Designed and implemented features enabling users to favorite categories as a precedent for personalized content recommendations, resulting in increased user engagement and streamed hours.

Software Engineer

June 2022 - Sept 2022

Amazon Alexa AI | Seattle, WA

• Contributed to the development and enhancement of an internal cutting-edge AI/ML solution that facilitates secure and privacy-preserving machine learning to iteratively explore, prepare, build, train, and deploy machine learning models using critical data.
• Collaborated in integrating a wide array of AWS services and Amazon-specific ML tools, delivering a comprehensive ecosystem that enables customer-specific ML innovations through well-defined APIs.

Data Science Intern

Dec 2021- Jun 2022

King County Metro | Seattle, WA

• Spearheaded the implementation of machine learning algorithms to predict King County Metro transit ridership, leveraging data collected from automated passenger counter sensors to provide insights into ridership patterns, enabling more efficient and responsive transit services.
• Analyzed 2.3 million instances of transit boarding data to inform strategic fare policy decisions using a data-driven approach.
• Presented findings to agency stakeholders and leadership; authored research paper on fare policy impacts to transit ridership.

Graduate Research Assistant

Sep 2021 - Jun 2022

Smart Transportation Applications and Research Lab | Seattle, WA

• Evaluated performance of deep-learning based traffic forecasting models and designed machine learning algorithm for accurate prediction of short-term traffic performance metrics for freeway networks to facilitate proactive traffic management.
• Analyzed data from network of 50,000 inductive loop detectors on freeways in Seattle to guide strategic decisions for optimizing traffic flow, enhancing safety, and streamlining transportation operations.

Graduate Research Assistant

Sep 2021 - Jun 2022

Intelligent Urban Transportation Systems Lab | Seattle, WA

• Spearheaded the development of a highly interactive web interface for modeling optimal electric bus charging infrastructure locations and quantities, providing an intuitive tool to make data-driven decisions in sustainable transit planning.
• Led a comprehensive analysis of a transit ridership dataset encompassing 650,000 transit boardings. Employed advanced data analytics and predictive modeling to forecast transit ridership for post-COVID return-to-work scenarios in the Puget Sound region.

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