A Data-Driven
01 — About Me
Hello, again
IgrewupinDhaka—acityoftwentymillionpeople,infinitetraffic,andbetterfoodthanwhereveryou'rereadingthisfrom.AteighteenIlandedinHalifaxforafinancedegreeatSaintMary's,whereImanagedareal$600KstudentfundandtooksecondplaceattheVentureCapitalInvestmentCompetitioninBoston.
Thencamesixyearswherefinanceanddatakeptcolliding:fundoperationsatCitco,thenRBCCapitalMarkets,whereIgrewfromDataAnalysttoSeniorDataAnalyst—buildingprojectionmodels,automatingreportingpipelines,andcuttinga13-minutedatapipelinedownto2.SomewhereinthereIalsobecameaCFALevel1candidate.
NowI'minMontréaldoingaMasterofManagementinAnalyticsatMcGill'sDesautels,goingdeeponthemachine-learningside:NLPonfinancialnews,computervisionforCanadianNationalRailway,andwhateverelseletsmebuildthingsthatmatter—someofthemforBangladesh.
- Currently
- MMA candidate @ McGill (Desautels)
- Previously
- Senior Data Analyst @ RBC Capital Markets
- Based in
- Montréal, Canada
- From
- Dhaka, Bangladesh
- Credential
- CFA Level 1 candidate
02 — What I do
What
I Do
Analyze
Description
Six years of making capital-markets data confess: projection models, SQL at scale, NLP on financial news, computer vision on live rail footage. If it has a signal, I'll find it.
Build
Description
Then I ship the answer: automated pipelines that cut 13 minutes to 2, production ML behind FastAPI and Docker, and DeshRide — a whole carpooling platform for Bangladesh.
03 — My CareerMy career & experience
Master of Management in Analytics
McGill University — Desautels Faculty of Management, Montréal
2025 — presentAwarded a 30% entrance scholarship. Projects: forecasting stock moves from news sentiment (ARIMA + BERT), predicting speed-dating success (GBM, k-NN), and an ongoing partnership with Canadian National Railway building real-time computer vision that flags rail-line deformities and wildfire risk from live video.
Senior Data Analyst
RBC Capital Markets, Halifax
2024 — 2025Built projection models and validation reporting on large relational databases; automated data-mining workflows that halved report generation time; optimized a core data pipeline from 13 minutes down to 2.
Data Analyst
RBC Capital Markets, Halifax
2022 — 2023Shipped a big-data Python program that went to production, and reported weekly to senior management through Tableau dashboards.
Operations Analyst
Citco Fund Services, Halifax
2021Fund services for multinational hedge funds and private equity — A/B, sensitivity and stability testing, client-facing decks, and a 20% ETL efficiency improvement from a data-validation investigation.
Fund Manager, TMT sector
Impact Fund, Sobey School of Business
2018 — 2020Managed the TMT book of a $600K student-run fund using DCF/DDM/comps on FactSet, Bloomberg and Capital IQ. Pitched the Maxar liquidation and the OpenText acquisition — both executed. Plus co-ops at Nova Scotia Power (energy forecasting) and East Coast Offshore Supplies.
Bachelor of Commerce, Finance
Saint Mary's University, Halifax
2016 — 2020GPA 3.88/4.30, Magna Cum Laude, Beta Gamma Sigma (top 7%). Placed 2nd at the Venture Capital Investment Competition in Boston. Graduated with Co-op Distinction.
04 — Works
My Work
DeshRide
Flagshipসমগ্র বাংলাদেশ — intercity carpooling for Bangladesh
A Poparide-style carpooling platform covering all 64 districts of Bangladesh. Drivers post trips they're already making; travellers book the empty seats. Payments are held in escrow via bKash, Nagad, or card — released only after the trip completes, designed around Bangladesh Bank's digital-commerce rules. Ships as an Android app with automated APK builds.
Rail Vision × CN
Real-time computer vision for Canadian National Railway
Ongoing McGill partnership with CN (NYSE: CNI): live video analytics that detect rail-line deformities and flag conditions that start track-side wildfires — models built for real-time inference on streaming footage.
Market Sentiment
Forecasting stock moves from financial news
Time-series forecasting (ARIMA) fused with BERT-based sentiment extracted from news coverage, testing whether headlines lead price action. Built during the McGill MMA — where finance experience meets NLP.
ML in Production — INSY 674
From notebook to deployed API
End-to-end ML predicting whether job candidates will change employers: research notebooks → production package → FastAPI with Pydantic validation → Docker → live on Render with drift monitoring. My contribution hardened the API contract with CI tests.
05 — Skillset & Tools
My Techstack
Analytics & Machine Learning
- Python
- SQL
- pandas / scikit-learn
- NLP (BERT)
- Time series (ARIMA)
- Computer vision
- Tableau
Finance & Markets
- Valuation (DCF · DDM · Comps)
- CFA Level 1 candidate
- FactSet · Bloomberg
- Capital IQ · Reuters
- Fund operations
- Quantitative research
Engineering & Tools
- TypeScript / React
- FastAPI
- Docker
- Git & GitHub Actions
- ETL pipelines
- SAS
06 — Beyond the résumé
Life, lately
ঢাকা → Halifax → Montréal
Dhaka gave me the hustle, Halifax gave me a finance degree and my first real winters, Montréal gave me bagels and machine learning. Three cities, one wardrobe crisis.
The soundtrack
The song playing right now is the 23 Theme by Anirudh Ravichander. It's what I put on when it's 2 a.m. and the model finally converges. Non-negotiable site feature.
Hear it on YouTube ↗I quantify everything
I'm an analytics person in the truest sense: I even log my bad habits to JSON. Exhibit A: AmrCigarateKhawaTracker.py — a Python tracker for how many cigarettes ami khaise. The data trends downward. Mostly.
The evidence, on GitHub ↗Red Cross roots
Before the spreadsheets: coordinating for the Red Cross. Some instincts — show up, organize the chaos, help — carried straight into how I work.