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.gitignore

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

content/resume/_index.md

@@ -3,112 +3,128 @@ title: "Resume"
 date: 2019-02-11T07:50:51-05:00
 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 %}}<!--- {{{ -->
 
+<!--- 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 {{{ -->
 
 {{% resume/project name="Rarity Surf" 
-languages="Python, JavaScript, React, Django"  
-date="Oct 2021" show="true" %}}
-
-- **Developed a full-stack web application** to generate rarity 
-  rankings for NFT's integrated with leading NFT 
-  marketplace's (OpenSea) API, 
-  enabling users to **quickly identify rare NFT's** and check 
-  their listing status, **improving market research efficiency by 80%**.
-- **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 (Javascript) 
-  [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%**.
+languages="Python, Django, JavaScript, React"  
+date="Oct 2022" show="true" %}}
 
+- **Built a full-stack reporting tool** using React, 
+  Django, and **PostgreSQL** to analyze 
+  structured/unstructured metadata from APIs, enabling 
+  real-time rarity scoring and improving insight 
+  delivery by **80%**.
+- **Optimized SQL query performance** within a 
+  Django-based pipeline, processing NFT ranking data at 
+  scale and exposing results via GraphQL with 
+  **low-latency response times under high concurrency 
+  (2,000+ queries)**.
 
 {{% /resume/project %}}
 
 <!--- Rarity Surf }}} -->
 
+{{% /resume/section %}}<!--- }}} -->
 
-<!--- Astronofty {{{ -->
+{{% resume/section "Work Experience" %}}<!--- {{{ -->
 
-{{% 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 80%** during the demo.
-
-{{% /resume/project %}}
-
-<!--- Astronofty }}} -->
+{{% 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 %}}<!--- {{{ -->
 
-**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 education %}}<!--- {{{ -->
 
 {{% resume/education name="University of Toronto (St. George)"
-title="Computer Science Specialist — 3.84 GPA (CS). Graduated with High Distinction." date="2019 — 2024" %}}
-
-{{% /resume/section %}}<!--- }}} -->
-
-{{% resume/section "References" %}}<!--- {{{ -->
-
-{{% resume/references %}}
+title="Computer Science Specialist - 3.84 GPA (CS). Graduated with High Distinction." date="2019 - 2024" %}}
 
 {{% /resume/section %}}<!--- }}} -->