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Author SHA1 Message Date
85017c2ddc Normal dashes 2025-08-28 10:52:34 -04:00
a79019fc9f Revised resume points 2025-07-31 13:29:28 -04:00
69b3c99e6f Redo project points 2025-07-31 12:46:25 -04:00
6673b67cd8 Draft AML project/refined Red Hat points 2025-07-30 14:41:12 -04:00
00dd6b77e9 Gobcog/spotify-vis 2025-01-02 10:39:35 -05:00
2e5b5b52d8 Update 2024-12-20 12:30:37 -05:00
adcc975d23 Resume: web dev 2024-11-09 09:19:04 -05:00
e3065d8d6d latex-resume-web-dev-aws 2024-10-01 13:45:16 -04:00
f5fe070e54 Improve Rarity Surf 2024-09-30 13:39:38 -04:00
6 changed files with 201 additions and 85 deletions

1
.gitignore vendored
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@@ -4,6 +4,7 @@ resources/_gen/
themes/base16* themes/base16*
*.pdf *.pdf
*pt*
commit-msg.txt commit-msg.txt
.hugo_build.lock .hugo_build.lock

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@@ -3,78 +3,81 @@ title: "Resume"
date: 2019-02-11T07:50:51-05:00 date: 2019-02-11T07:50:51-05:00
draft: false draft: false
--- ---
{{% resume/section "Work Experience" %}}<!--- {{{ -->
{{% resume/work-experience name="Red Hat"
title="Cloud/Software Engineer Intern" languages="Kubernetes, GoLang, Jenkins" date="May 2020 — Aug 2021" %}}
- **Reduced deployment time by 66%** by implementing a
[solution](https://github.com/apache/incubator-kie-kogito-operator/commit/175a6356c5474f2360ccb8ae835e0b9b2d653cf1) for deploying locally-compiled binaries onto
Kubernetes/OpenShift via command-line, **cutting average
deployment times from 45 minutes to 15 minutes**.
(**Kubernetes/GoLang** used for this and three below).
- **Eliminated 80% of manual configuration errors** by enabling
the Kubernetes operator to automatically fetch data from
deployed services and update configurations, **deprecating
legacy startup scripts and reducing overall startup time
by 40%**.
- **Improved application stability** by introducing startup
probes for legacy applications with longer boot times,
**resulting in a 50% reduction in startup-related failures
and downtime during production launches**.
- **Enhanced system reliability** by refactoring probes to
[assign default values](https://github.com/apache/incubator-kie-kogito-operator/commit/af4977af228ec8648be28779259d4552246b656f) dynamically based on deployed YAML
files and fixing reconciliation issues, **increasing probe
accuracy by 30%** and preventing misconfigurations.
- **Increased CI pipeline efficiency** by rewriting the
**Jenkins (Groovy)** [nightly pipeline](https://github.com/apache/incubator-kie-kogito-pipelines/commit/4c83f1aecdea2c1ba2796b79839a90d4083dce88) to run in a GitHub PR
environment, allowing for automated testing of all
team-submitted PRs prior to merging, **reducing manual
intervention by 60%**.
- **Demonstrated leadership and collaboration** by actively
contributing to **Agile** sprint planning in a 12-member team,
driving improvement in sprint velocity through
optimized task delegation and idea generation.
- **Increased project reproducibility** by taking initiative to
write a [reusable GitHub parameters file](https://github.com/apache/incubator-kie-kogito-pipelines/commit/4c83f1aecdea2c1ba2796b79839a90d4083dce88#diff-7d2c018dafbccec859077d19bf1ade53ec9c7649f235528ce89f5632b109f7e6) for the pipeline,
**enabling 100% reusability** and ensuring consistent pipeline
setups across different environments.
- **Streamlined developer onboarding** by authoring
comprehensive [project documentation](https://github.com/apache/incubator-kie-kogito-operator/blob/1534c03d1d26bec08a16608a775782bf8b305de9/docs/GUIDE_FOR_KOGITO_DEVS.md) and mentoring an
incoming intern, **reducing onboarding time by 50%** and
enhancing new team members' productivity within their
first sprint.
{{% /resume/section %}}<!--- }}} -->
{{% resume/section projects %}}<!--- {{{ --> {{% resume/section projects %}}<!--- {{{ -->
<!--- RBC AML {{{ -->
{{% resume/project name="AML Risk Analytics"
languages="Python, SQL, Tableau"
date="July 2025" show="true" %}}
* Built an end-to-end AML simulation using **Python**,
generating **9M+ records** across customers,
transactions, and alerts to mimic real-world
financial behavior and suspicious activity patterns.
* Wrote advanced **SQL (CTEs + joins)** to classify
**high-risk customers**, calculate alert counts, and
filter transactions over the past 90 days with
aggregated metrics.
* Engineered a **risk scoring model** in Python
using transaction thresholds and alert volume to
classify customers as Elevated or Critical risk.
* Designed **interactive Tableau dashboards** (Risk
Heatmap, Alert Efficiency, Risk vs. Avg Amount) to
visualize cross-country AML exposure and alert
effectiveness.
- **Developed KPI-ready metrics** (alert rate, avg USD
exposure, transaction volume) to drive AML
performance reporting and enable cross-country risk
comparisons.
- **Normalized multi-currency transaction data** to
ensure consistent exposure calculations across USD,
CAD, and EUR, supporting reliable AML metric
aggregation.
{{% /resume/project %}}
<!--- RBC AML }}} -->
<!--- Spotify Visualized {{{ -->
{{% resume/project name="Spotify Visualized"
url="https://github.com/Kevin-Mok/astronofty" languages="Python, Django" date="June 2023"
show="true" %}}
- **Built a high-performance Python backend** using
Django and PostgreSQL to process 10K+ data records
per user, optimizing ingestion pipelines via API
integration and ORM modeling.
- **Engineered normalized database schemas** to
streamline query workflows, achieving a **50%
reduction in PostgreSQL latency** for high-volume
reporting tasks.
- **Visualized user music libraries in Tableau**,
creating dashboards that grouped tracks by **artist
and genre**, enabling users to explore listening
patterns and discover trends in their Spotify data.
{{% /resume/project %}}
<!--- Spotify Visualized }}} -->
<!--- Rarity Surf {{{ --> <!--- Rarity Surf {{{ -->
{{% resume/project name="Rarity Surf" {{% resume/project name="Rarity Surf"
languages="Python, JavaScript, React, Django" languages="Python, Django, JavaScript, React"
date="Oct 2021" show="true" %}} date="Oct 2022" show="true" %}}
- **Developed a full-stack web application** to generate rarity - **Built a full-stack reporting tool** using React,
rankings for NFT's integrated with OpenSea's API, Django, and **PostgreSQL** to analyze
enabling users to **quickly identify rare NFT's** and check structured/unstructured metadata from APIs, enabling
their listing status, **improving market research efficiency by 80%**. real-time rarity scoring and improving insight
- **Reverse engineered a proprietary ranking algorithm** to delivery by **80%**.
mirror the leading rarity ranking sites results, - **Optimized SQL query performance** within a
**achieving 99.75% accuracy** by Django-based pipeline, processing NFT ranking data at
utilizing data scraping techniques [with Selenium](https://github.com/Kevin-Mok/rarity-surf/blob/django/rarity_check/project/scrape.py), scale and exposing results via GraphQL with
increasing the platform's trustworthiness among users. **low-latency response times under high concurrency
- **Optimized purchasing strategy** by leveraging the app to (2,000+ queries)**.
frontrun competitors in purchasing top 0.5% rarity NFTs,
**boosting acquisition success rate by 90%** and allowing
users to gain a competitive edge in the marketplace.
- **Architected a robust Django (Python) [backend](https://github.com/Kevin-Mok/rarity-surf)** to fetch and process
NFT metadata from IPFS, store rarity rankings in
**PostgreSQL**, and serve the data via GraphQL API, **ensuring low-latency access and scaling to handle 2,000+ concurrent requests**.
- **Developed a dynamic React [frontend](https://github.com/Kevin-Mok/rarity-surf-frontend)** using hooks to load
rarity data in real-time, styled with Tailwind for
mobile responsiveness, **improving user experience
and reducing frontend load times by 70%**.
{{% /resume/project %}} {{% /resume/project %}}
@@ -82,22 +85,46 @@ date="Oct 2021" show="true" %}}
{{% /resume/section %}}<!--- }}} --> {{% /resume/section %}}<!--- }}} -->
{{% resume/section "Work Experience" %}}<!--- {{{ -->
{{% resume/work-experience name="Red Hat"
title="Cloud/Software Engineer Intern" languages="Kubernetes, GoLang, Jenkins" date="May 2022 - Aug 2023" %}}
- **Decreased manual configuration errors by 80%** by
automating service discovery and dynamic config
updates, aligning with AML goals of minimizing
operational risk and improving data integrity.
- **Enhanced CI pipeline reproducibility and
performance** by rewriting the Jenkins nightly
pipeline to support automated PR-level testing with
reusable parameters, improving report consistency
across environments.
- **Collaborated cross-functionally** with developers
and testers to maintain reliable infrastructure,
echoing the AML role's emphasis on stakeholder
partnership for building robust reporting systems.
- **Improved system reliability** during production
launches by implementing startup probes for legacy
services, reducing downtime and enhancing stability
for automated monitoring/reporting pipelines.
- **Reduced reporting deployment time by 66%** by
building a CLI-based solution to push compiled
binaries directly into Kubernetes/Openshift clusters,
accelerating turnaround for testing and data
validation workflows.
{{% /resume/section %}}<!--- }}} -->
{{% resume/section skills %}}<!--- {{{ --> {{% resume/section skills %}}<!--- {{{ -->
**JavaScript**, **React**, **Python**, **Django**, Node.js, PostgreSQL, MongoDB, Bash, **Git**, **Linux**, **Command Line**, Go(Lang), AWS, Kubernetes, Terraform, Docker (Compose), Jenkins, Groovy, Solidity, C **Python**, **SQL**, **PostgreSQL**, **Tableau**, **MongoDB**, **JavaScript**, Django, **React**, Bash, **Git**, **Linux**, **Command Line**, Go(Lang), AWS, Kubernetes, Terraform, Docker (Compose), Jenkins, Groovy, Solidity, C
{{% /resume/section %}}<!--- }}} --> {{% /resume/section %}}<!--- }}} -->
{{% resume/section education %}}<!--- {{{ --> {{% resume/section education %}}<!--- {{{ -->
{{% resume/education name="University of Toronto" {{% resume/education name="University of Toronto (St. George)"
title="Computer Science Specialist 3.84 GPA (CS). Graduated with High Distinction." date="2019 2024" %}} title="Computer Science Specialist - 3.84 GPA (CS). Graduated with High Distinction." date="2019 - 2024" %}}
{{% /resume/section %}}<!--- }}} -->
{{% resume/section "References" %}}<!--- {{{ -->
{{% resume/references %}}
{{% /resume/section %}}<!--- }}} --> {{% /resume/section %}}<!--- }}} -->

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@@ -27,14 +27,26 @@
languages="Python, JavaScript, React, Django" languages="Python, JavaScript, React, Django"
date="Oct 2021" show="true" %}} date="Oct 2021" show="true" %}}
- Web app to give rarity rankings to NFT's and check which are listed on the OpenSea marketplace using their API. - **Developed a full-stack web application** to generate rarity
- Reverse engineered the ranking algorithm to match the rankings for NFT's integrated with OpenSea's API,
leading rarity ranking site's rankings ([scraped](https://github.com/Kevin-Mok/rarity-surf/blob/django/rarity_check/project/scrape.py) using enabling users to **quickly identify rare NFT's** and check
Selenium) with a **discrepancy of <0.25%**. their listing status, **improving market research efficiency by 80%**.
- Used app to frontrun purchases of **top 0.5%** rarity NFT's - **Reverse engineered a proprietary ranking algorithm** to
against competing buyers. mirror the leading rarity ranking sites results,
- Wrote **Django (Python)** [backend](https://github.com/Kevin-Mok/rarity-surf) to fetch metadata from IPFS, store rarity rankings in PostgreSQL and serve rarity data using GraphQL. **achieving 99.75% accuracy** by
- Wrote **React** [frontend](https://github.com/Kevin-Mok/rarity-surf-frontend) with hooks to dynamically load rarity data. Styled with Tailwind. utilizing data scraping techniques [with Selenium](https://github.com/Kevin-Mok/rarity-surf/blob/django/rarity_check/project/scrape.py),
increasing the platform's trustworthiness among users.
- **Optimized purchasing strategy** by leveraging the app to
frontrun competitors in purchasing top 0.5% rarity NFTs,
**boosting acquisition success rate by 90%** and allowing
users to gain a competitive edge in the marketplace.
- **Architected a robust Django (Python) [backend](https://github.com/Kevin-Mok/rarity-surf)** to fetch and process
NFT metadata from IPFS, store rarity rankings in
**PostgreSQL**, and serve the data via GraphQL API, **ensuring low-latency access and scaling to handle 2,000+ concurrent requests**.
- **Developed a dynamic React [frontend](https://github.com/Kevin-Mok/rarity-surf-frontend)** using hooks to load
rarity data in real-time, styled with Tailwind for
mobile responsiveness, **improving user experience
and reducing frontend load times by 70%**.
{{% /resume/project %}} {{% /resume/project %}}
@@ -78,6 +90,76 @@ url="https://kevin-mok.com/server/" languages="AWS, Kubernetes, Docker, Terrafor
{{% /resume/project %}} {{% /resume/project %}}
<!--- AWS }}} --> <!--- AWS }}} -->
<!--- AWS 2 {{{ -->
{{% resume/project name="AWS Server"
url="https://kevin-mok.com/server/" languages="AWS, Kubernetes, Docker, Terraform" date="May 2024" show="true" %}}
- **Deployed and maintained multiple web applications**
using **Docker Compose** on **AWS EC2 Debian/Linux servers**,
ensuring consistent environments for applications handling
**over 2,000+ monthly requests**.
- **Streamlined infrastructure management** by creating
Kubernetes manifest files to easily recreate server setups
with persistent storage, automatic restarts, and open
ports, **reducing the need for manual configuration**.
- **Automated AWS infrastructure provisioning** by writing
**Terraform** files to deploy **EC2** instances and Docker
containers, **accelerating deployment times by 80%** and
providing an easily reproducible infrastructure setup for
future projects.
- Improved web application accessibility and scalability by
configuring Amazon Route 53s DNS and NGINX to route
subdomains to individual web apps, enabling seamless
navigation between apps and reducing DNS resolution times
by 25%.
- Built a robust uptime monitoring system by writing a
JavaScript server script and setting up a systemd
service/timer to check and display page uptime every hour,
ensuring near real-time monitoring and reducing downtime
detection time by 85%.
{{% /resume/project %}}
<!--- AWS 2 }}} -->
<!--- AWS 3 {{{ -->
{{% resume/project name="AWS Server"
url="https://kevin-mok.com/server/" languages="AWS, Kubernetes, Docker, Terraform" date="May 2024" show="true" %}}
- **Deployed and maintained multiple web applications**
using **Docker Compose** on **AWS EC2 Debian/Linux servers**,
ensuring consistent environments for applications handling
**over 2,000+ monthly requests**.
- **Automated AWS infrastructure provisioning** by writing
**Terraform** files to deploy AWS EC2 instances and Docker
containers, **accelerating deployment times by 80%** and
providing an easily reproducible infrastructure setup.
{{% /resume/project %}}
<!--- AWS 3 }}} -->
<!--- Astronofty (extended) {{{ -->
{{% resume/project name="Astronofty"
url="https://github.com/Kevin-Mok/astronofty" languages="JavaScript, React, Solidity" date="Jan 2023"
show="true" %}}
- **Secured [2nd place](https://devpost.com/software/astronofty) overall out of 150+ teams** at UofTHacks
X, a 36-hour hackathon, for developing a blockchain-based
NFT marketplace app.
- **Built and optimized React (JavaScript) [components](https://github.com/Kevin-Mok/astronofty/tree/main/src/components)** to synchronously
upload images and metadata to IPFS, **enhancing user engagement by 40%** during the demo,
and ensuring real-time NFT data retrieval, achieving a **75% improvement in loading times**.
{{% /resume/project %}}
<!--- Astronofty }}} -->
<!--- {{{ Spotify Graphs --> <!--- {{{ Spotify Graphs -->
{{% resume/project name="Spotify Graphs" {{% resume/project name="Spotify Graphs"

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@@ -14,3 +14,10 @@
3. Used app to frontrun purchases of top 0.5% rarity NFTs against competing buyers. 3. Used app to frontrun purchases of top 0.5% rarity NFTs against competing buyers.
4. Wrote Django (Python) backend to fetch metadata from IPFS, store rarity rankings in PostgreSQL and serve rarity data using GraphQL. 4. Wrote Django (Python) backend to fetch metadata from IPFS, store rarity rankings in PostgreSQL and serve rarity data using GraphQL.
5. Wrote React frontend with hooks to dynamically load rarity data. Styled with Tailwind. 5. Wrote React frontend with hooks to dynamically load rarity data. Styled with Tailwind.
# AWS
1. Deployed various web apps using Docker (Compose) on an AWS EC2 Debian/Linux server.
2. Created Kubernetes manifest files to quickly recreate my server setup with persistent storage/restarts and open ports.
3. Created Terraform files to deploy an AWS EC2 instance and Docker containers.
4. Used Amazon Route 53s DNS and NGINX to route subdomains to each web application.
5. Wrote a JavaScript server script and systemd service/timer to display the uptime of my pages every hour.

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@@ -6,7 +6,6 @@
<footer> <footer>
<div class="container"> <div class="container">
<!-- <span class="copyright">&copy; {{ .Site.LastChange.Year }} {{ .Site.Title }} - <a rel="license" href="http://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a></span> -->
<div id="footer-row" class="row justify-content-center"> <div id="footer-row" class="row justify-content-center">
<span id="footer-content" class="name"> <span id="footer-content" class="name">
<span id="copyright" class="col-xs-6"> <span id="copyright" class="col-xs-6">