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@ -22,41 +22,49 @@ date="July 2025" show="true" %}} |
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<!--- RBC AML }}} --> |
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<!--- Rarity Surf {{{ --> |
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<!--- Spotify Visualized {{{ --> |
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{{% resume/project name="Rarity Surf" |
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languages="Python, Django, JavaScript, React" |
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date="Oct 2024" show="true" %}} |
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{{% resume/project name="Spotify Visualized" |
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url="https://github.com/Kevin-Mok/astronofty" languages="Python, Django" date="June 2023" |
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show="true" %}} |
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- **Developed a full-stack web application** to generate rarity |
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rankings for NFT's integrated with leading NFT |
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marketplace's (OpenSea) API, |
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enabling users to **quickly identify rare NFT's** and check |
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their listing status, **improving market research efficiency by 80%**. |
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- **Architected a robust Django (Python) [backend](https://github.com/Kevin-Mok/rarity-surf)** to fetch and process |
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NFT metadata from IPFS, store rarity rankings in |
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**PostgreSQL**, and serve the data via GraphQL API, **ensuring low-latency access and scaling to handle 2,000+ concurrent requests**. |
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- **Built a high-performance Python backend** using |
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Django and PostgreSQL to process 10K+ data records |
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per user, optimizing ingestion pipelines via API |
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integration and ORM modeling. |
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- **Engineered normalized database schemas** to |
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streamline query workflows, achieving a **50% |
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reduction in PostgreSQL latency** for high-volume |
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reporting tasks. |
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- **Visualized user music libraries in Tableau**, |
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creating dashboards that grouped tracks by **artist |
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and genre**, enabling users to explore listening |
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patterns and discover trends in their Spotify data. |
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{{% /resume/project %}} |
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<!--- Rarity Surf }}} --> |
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<!--- Spotify Visualized {{{ --> |
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<!--- Spotify Visualized }}} --> |
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{{% resume/project name="Spotify Visualized" |
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url="https://github.com/Kevin-Mok/astronofty" languages="Python, Django" date="June 2022" |
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show="true" %}} |
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<!--- Rarity Surf {{{ --> |
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- **Built a [high-performance backend](https://github.com/Kevin-Mok/spotify-lib-vis)** in Python with Django, |
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utilizing Django ORM to model and manage user data |
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efficiently, processing over **10,000 tracks per library** via |
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the Spotify API. |
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- **Engineered and optimized database models** achieving a **50% reduction in query latency** on PostgreSQL |
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for core workflows through effective schema normalization. |
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{{% resume/project name="Rarity Surf" |
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languages="Python, Django, JavaScript, React" |
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date="Oct 2022" show="true" %}} |
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- **Built a full-stack reporting tool** using React, |
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Django, and **PostgreSQL** to analyze |
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structured/unstructured metadata from APIs, enabling |
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real-time rarity scoring and improving insight |
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delivery by **80%**. |
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- **Engineered a scalable data pipeline** in Django |
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(Python) to ingest, process, and expose NFT ranking |
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data via GraphQL, supporting **low-latency |
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reporting** and scaling to **2,000+ concurrent |
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queries** for end-user research. |
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{{% /resume/project %}} |
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<!--- Spotify Visualized }}} --> |
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<!--- Rarity Surf }}} --> |
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{{% /resume/section %}}<!--- }}} --> |
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