DYOR is a platform designed to help users minimize investment risks in the Crypto and Equity markets by offering tools for portfolio management, investment research, and simulated trading. It also provides insights through sentiment analysis of social media and news aggregation, and aims to introduce price prediction using machine learning to better guide investment decisions. [github]
Sashank Silwal
शशांक सिलवाल
Hello, I'm Sashank. As a data scientist specializing in risk analytics, I focus on fraud detection and prevention using advanced machine learning techniques. With a strong foundation in data science, big data management, and analytics, I bring my expertise to Binance, where I contribute to the Risk AI team.
I hold a Bachelor of Science degree in Computer Science from New York University Abu Dhabi (NYU Abu Dhabi), graduating with Honors. My academic journey included a focus on machine learning, software enginnering, and interactive media, equipping me with a versatile approach to solving complex data challenges.
Professional Experience
Data Scientist - Binance
- Developing models as part of the Risk AI team
Data Analyst: Growth - Bearaby®
- Executed comprehensive market analysis for weighted blankets in Europe, developing a data-driven entry strategy targeting an 8% market share in the DTC and e-commerce sectors
- Conducted A/B testing to refine product attachment rates, significantly boosting cross-sell and up-sell strategies
- Analyzed customer purchase behaviors using BigQuery, achieving a 16% boost in targeted marketing effectiveness
- Engineered data pipelines and dashboards to define and track KPIs, driving business growth and improving key metrics by 15%
Software Engineering Intern - Vanilla®
- Enhanced in-app user experience by designing React components, boosting user engagement by 7%
- Streamlined the GraphQL layer, improving retrieval and update times for PostgreSQL attributes by 30%
- Collaborated with the Product Team on the engineering design doc to implement three new service-driven backend features
- Maintained and updated unit tests and end-to-end tests using Minitest and Cypress to ensure code coverage higher than 85%
Research Experience
Research Assistant - CommNets Lab: NYU Abu Dhabi
Supervision of Prof. Yasir Zaki
- Engineered and deployed a neural network model using Kotlin on a mobile browser to classify and block JavaScript code, resulting in a 27% improvement in web page load time for underserved countries.
- Compiled a comprehensive dataset of 127,000 JavaScript elements labeled with categories by extracting 500,000 elements from 20,000 popular web pages
Research Intern - Center For Global Sea Level Change: New York University
Supervision of Prof. David Holland and Dr. Daiane Gracieli Faller
- Developed and assessed a Bayesian probabilistic model to predict long-term shoreline changes based on geomorphological and geological conditions under various sea level rise scenarios
Research Fellow(PPTP) - Center for Quantum and Topological Systems (CQTS)
Supervision of Prof. Hisham Sati
- Exploring how the dependently typed programming language Agda can be used to formalize braid groups as automorphisms of free groups
Selected Projects
The app is a marketplace designed specifically for NYU students on the Manhattan and Brooklyn campuses to buy and sell items such as coursework notes, textbooks, and furniture. It includes recommendation features to help users discover new items relevant to their needs and interests. [github]
The project explores the influence of demographic data of the cast, such as ethnicity, gender, age, and star power, on the global box office of movies. Results show that movies with more diverse casts tend to make lower profits than those with mostly white casts, and that actors have a higher presence in movies than actresses. [github]