shresh.ca
live
$ cat about.md · about.md
// $ whoami

shresh.ca

developer · data tools

>

i'm a data scientist at RBC and a math + cs / bba double-degree student at the university of waterloo and wilfrid laurier.

on the side i build small, useful things — mostly data tools, scrapers, and web apps. most of them start as "i wish this existed" and end up on the internet a few weekends later.

currently into competitive valorant analytics, ebook discovery, and porting cool unix-y tools to windows.

$ cat projects.json · projects.json
  • vlr-api

    pythonscrapingcodex-apiself-healing

    unofficial vlr.gg API for live + historical valorant stats — ratings, clutch %, first kills, team rankings, match data, all filterable by tournament/region. self-heals when vlr.gg breaks: catches the error, asks codex to find the new selectors, and re-points the scraper.

  • bookwormd

    webnextscraping

    browse bestsellers and find free downloads. made anna’s archive easy to browse so you never have to pay for an ebook again.

  • clicky-windows

    windowsdesktopopen-source

    windows port of @FarzaTV’s clicky. saw it, thought it was cool, built it for windows. cleanup + open-source pass in progress.

  • val-events-radars

    pythonstreamlitdata-viz

    pulls + updates valorant pro player data and renders comparable radar charts per event. fast, lightweight, deployed on streamlit.

$ cat resume.md · resume.md

// experience

  1. Data Scientist @ RBC

    Dec 2025 — present · permanent part-time · hybrid
  2. Data Scientist (Co-op) @ RBC

    Aug 2025 — Dec 2025 · hybrid
  3. Data Analyst (Co-op) @ RBC

    Jan 2025 — Apr 2025 · hybrid
    • piloted a contextual multi-armed bandit + RL framework for offer control testing, optimizing personalized offer splits across client segments.
    • automated tableau dashboards via snowflake drivers — killed the manual reporting cycle.
    • analyzed multi-year distributions of avion points earned/burned to identify top cohorts and inform loyalty strategy.
    • produced insights + custom reports for loyalty, cards, and finance teams — offer investment analysis, linked client segmentation.
    • stack: python (pandas, spark), sql (teradata, trino, snowflake), jupyter.

// education

  • University of Waterloo 2022 — 2027
    Mathematics and Computer Science
  • Wilfrid Laurier University · Lazaridis School of Business 2022 — 2027
    BBA, Business Administration and Management

// stack

languages python · sql · typescript · javascript
frameworks pandas · spark · streamlit · next.js · astro · fastapi
tools snowflake · teradata · trino · tableau · cloudflare · git · docker
$ cat music.json · music.json
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    $ ls -lt blog/ · blog.md
    $ cat contact.md · contact.md