Aditya Arora

Computer Engineering @ University of Waterloo - graduating 2022

Aditya Arora is a highly motivated Computer Engineering student at the University of Waterloo, set to graduate in 2022. With a passion for problem-solving and software development, Aditya is constantly exploring the latest technologies in the field, including blockchain, deep learning, and

2.1

Years of Experience

Education

university of waterloo

Companies

wish, department of electrical computer engineering university of waterloo, wish, wish, kitchenmate, draper ai, university of waterloo, sage co, lcbonext, watonomous

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Experience

2021 - Present
wish
Data Scientist
2021 - 2021
department of electrical computer engineering university of waterloo
Software Engineer - Research Assistant
- Working under Prof. Derek Wright to build a internal platform using Postgres, Node and React for managing the ECE departments’ CEAB requirements
2021 - 2021
wish
Data Scientist
- Built a 94% accurate model to predict the probability of the user refunding an item within 90 days - Reduced refund abuse by developing a single scoring mechanism for each user to accurately reflect the abuse by them and their linked accounts against Wish refund policies - Improved revenue by using XGBoost to conduct explainable user segmentation to isolate clusters of users that purchase up to 10x more from user generated content
2020 - 2020
wish
Software Engineer
- Improved transaction success by 3% for an annualized improvement in GMV by $15M by setting up remove item retry mechanism for insufficient fund transactions - Improved traceability of fraudulent actors by marking user sessions with a multi-factor authentication session key to log high risk events - Increased average customer satisfaction by 3% by designing a user flow to allow users to change their payment method after placing an order - Setup infrastructure using Pytest fixtures to enable improved testing coverage for key code paths - Reduced fraud through post-purchase address change by incorporating address verification flows
2019 - 2019
kitchenmate
Software Engineer
- Improved legibility and reduced frame jitter by 50% by adding support for on device text and animation rendering on new display on proprietary cooker - Built an internal top level overview dashboard in Metabase to allow for effective and efficient decision making process on our corporate customers in a single glance - Improved customer food satisfaction by 30% by devising a data driven approach to menu design by analyzing dish reviews to isolate a metric to define the popularity of a dish - Set up an internal data science pipeline to enable data driven decisions at each level of the business
2019 - 2019
draper ai
Data Engineer
- Working to improve the keyword bidding algorithm to better target Amazon ads - Reduced customer onboarding time by 15% by building a new tool for Account Executives to entice new customers - Using BigQuery and Pandas/Python to generate valuable insights from customer data - Built internal tools to detect system downtime using SQL and Metabase - Escalated and fixed 3 high level production environment bugs
2018 - 2018
university of waterloo
Research Assistant in Pattern Analysis and Machine Intelligence
- Building a NLP chatbot in Python and Dialogflow for grocery chain Loblaws under Prof Fakhri Karray to allow customers to ask contextual questions while in store - Ported over existing from slower excel sheet frameworks to PostGresQL to improve net performance by 30% - Developed a low latency API endpoint in Python from scratch to serve Loblaws customers
2018 - 2021
sage co
Partner, Technology Lead
- Designing the online presence and building websites for SMBs in North America (portfolio to date includes community websites, local newspapers, law firms, and small print shops) - Responsible for managing the technical direction of the company, and leading the charge on all things technical - Services include branding, web design & development, custom CMS, website audits, Shopify stores, and SEO optimization
2018 - 2018
lcbonext
Full-stack Developer + Data Science Coop
- Wrote complete CRUD web apps and REST APIs from scratch with less than 0.1% downtime to serve data to multiple internal applications to serve LCBOs customers - Managed and maintained the sole Kubernetes cluster running an Elasticsearch instance - Implemented an 85% accurate sales forecasting model from scratch to anticipate uptick in sales of products after incorporating the weather forecast - Visualised and analysed sales trends at top retail locations to classify products into priority based classes to support LCBO’s retail and supply chain divisions
2018 - 2018
watonomous
Perception Core Member
- Core Member of the perception team as part of GM’s AutoDrive Challenge - Implemented a 5% more efficient model to identify lane markings in OpenCV - Improved existing traffic sign detection computer vision models in Tensorflow by 15% using hyper-parameter tuning and regularization - Consolidated data for one way stop signs along with annotations utilising publicly available datasets