Data Analyst
Baseline · Toronto
Working with data, analysis, and reporting to help teams make clearer decisions.
Data analyst at Baseline · Toronto
Building useful things with data and AI.
I’m Krrish, a data analyst growing into an AI engineer. I turn messy data, models, and experiments into systems people can use.
Machine learning✦AI engineering✦Data storytelling✦Useful systems✦Learning in public✦Machine learning✦
Selected work
Projects with a point of view.
The problems I chose, the trade-offs I made, and what the results taught me. Each project now opens into the full case study.
/01
Machine learning · Python
A fraud detector designed around the cost of being wrong.
A risk-focused model for a heavily imbalanced dataset, built to catch more fraud without burying reviewers in false alarms.
- <0.2% fraud
- ~84% CV F1
- 0.4 review threshold
/02
Predictive analytics · Python
Turning churn predictions into business decisions.
Feature engineering, model comparison, and business analysis for finding which customers may leave and what a retention team could do next.
- 10k customers
- 6 models
- 0.63 F1
/03
Simulation · R
72,000 possible retirements, one clearer decision.
A Monte Carlo model testing when Canadians should draw OAS under different lifespans, account types, tax rules, and market conditions.
- 72k simulations
- Ages 65–70
- RRSP + TFSA
Experience
Business context, then data, now AI.
The path is still moving. Each step has added a different way to understand and build useful systems.
BBA
Schulich School of Business
Built a foundation in business analytics and finance before moving deeper into technical work.
AI engineering
Independent projects
Learning production AI systems through evaluation, data pipelines, interfaces, and public build logs.
Field notes
What the model score left out.
Short notes about experiments, mistakes, decisions, and what changed after looking closer.
Model notes · 5 min read
What ROC-AUC hid in my fraud-detection project
The throughline
BBA → Data → AIBusiness context taught me what matters. Data taught me how to measure it. Now I’m learning how to build around it.
I started in business analytics and finance at Schulich, then moved deeper into SQL, Python, forecasting, machine learning, and data products. Today I work as a data analyst at Baseline.
I’m interested in the space between a convincing notebook and a dependable product: evaluation, data pipelines, model behaviour, and interfaces that make complex systems easier to understand.