CHAPTER 00 — ENTRY POINT

MARIAMREHAN

Insights Analyst (fr)

I make pretty charts and tell stories. with them

hover for the truthyou're gonna love my work
Analyst.Storyteller.Chaotic Good.Data Witch.Anime Enjoyer.Pattern Hunter.Spreadsheet Sorcerer.Zine Collector.Analyst.Storyteller.Chaotic Good.Data Witch.Anime Enjoyer.Pattern Hunter.Spreadsheet Sorcerer.Zine Collector.
SCROLL

CHAPTER 01 — CHARACTER FILE

CHARACTERFILE

RPG stats for an analyst who treats messy datasets like side quests and suspicious insights like plot twists.

RPG STAT SHEET

テレパシー
Curiosity99/100
Café Hours Logged87/100
Pattern Recognition95/100
Overthinking Simple Things91/100
Tolerance for Bad Data Viz12/100

EQUIPPED:

— ANALYSEPythonSQLSPSS
— VISUALISEPower BITableauExcel
CURRENTLY: Analysing consumer behaviour @ AiSight · Karachi

847

Excel Sheets Survived

2,341

Anime Episodes Watched

3.65

CGPA (Merit Scholar)

1

Research Paper @ DDW 2026

10

Cities of Consumer Data Analysed

Class: Insight Mage / Subclass: Spreadsheet Bard

ORIGIN: Institute of Business Management, Karachi · BSc Data Science · Merit Scholarship Recipient

PortraitPROFILE PIC✦ 847 XP

CHAPTER 02 — CASE FILES

THE JOURNEY

Every dataset has a story. Here are the ones I've told.

CASE 00MASTER FILE

Want the full picture? Here's the complete file.

Mariam Rehan · Insights Analyst · Karachi

ACCESS FILE
CASE 01ACTIVE

Brands were bleeding customers — but not to competitors. I found where they were actually going.

AiSight · Insights Analyst · Feb 2026–present

Brand switching decomposition across multi-city consumer panels — separating competitive loss from category-level demand shifts so commercial teams could stop solving the wrong problem.
ExcelConsumer PanelsPivot TablesDirector-level Presentations

THE INSIGHT:

Brand switching decomposition across multi-city consumer panels — separating competitive loss from category-level demand shifts so commercial teams could stop solving the wrong problem.

CASE 02PUBLISHED

A forecasting model for cancer mortality trends — submitted to a global medical conference.

Broad Peak Lab · Research Assistant · Nov 2025–Jan 2026

Built an ARIMA time-series model projecting U.S. IBD-associated cancer mortality through 2035 using CDC WONDER epidemiological data. Findings submitted to Digestive Disease Week (DDW) 2026.
PythonARIMACDC WONDEREpidemiology

THE INSIGHT:

Built an ARIMA time-series model projecting U.S. IBD-associated cancer mortality through 2035 using CDC WONDER epidemiological data. Findings submitted to Digestive Disease Week (DDW) 2026.

CASE 03

Built an AI that turns messy PDFs into structured, usable forms — at scale.

Stagger Labs · Full Stack AI Engineer Intern · Jun–Oct 2025

Engineered a PDF-to-structured-form pipeline using GPT-4o, Python and Node.js — semantic field grouping, multi-page merging, incrementally ordered output. Production-grade infrastructure, not a school project.
PythonNode.jsGPT-4oLLM Orchestration

THE INSIGHT:

Engineered a PDF-to-structured-form pipeline using GPT-4o, Python and Node.js — semantic field grouping, multi-page merging, incrementally ordered output. Production-grade infrastructure, not a school project.

CASE 04

Predicted air quality 3 days out — so communities could act before the smog arrived.

10Pearls · Data Science Intern · Dec 2024–Feb 2025

XGBoost forecasting engine with serverless MLOps — hourly weather scraping, automated retraining, CI/CD pipeline, live Streamlit dashboard. Built as an intern. Runs like a product.
XGBoostHopsworksGitHub ActionsStreamlitMLOps

THE INSIGHT:

XGBoost forecasting engine with serverless MLOps — hourly weather scraping, automated retraining, CI/CD pipeline, live Streamlit dashboard. Built as an intern. Runs like a product.

CASE 05

Pakistani citizens needed a way to report broken infrastructure. So I built one.

Personal Project · Sheher Sunta Hai

Full-stack civic issue reporting platform — interactive heatmap, bilingual UI, real geocoding with OpenStreetMap. Roads, waste, water. Built for Pakistan, by someone from Karachi who gets it.
ReactPostgreSQLLeafletTypeScriptNode.js
View Project →

THE INSIGHT:

Full-stack civic issue reporting platform — interactive heatmap, bilingual UI, real geocoding with OpenStreetMap. Roads, waste, water. Built for Pakistan, by someone from Karachi who gets it.

CASE 06

Taught 'Build Your First Dashboard' to women in tech — because data literacy shouldn't have gatekeepers.

AI Datayard · Market Analyst Trainee · Dec 2024–Feb 2025

Designed and delivered a Power BI training session — accessible colour palettes, beginner-friendly datasets, visual storytelling principles. Community upskilling as a form of advocacy.
Power BIData StorytellingCommunity

THE INSIGHT:

Designed and delivered a Power BI training session — accessible colour palettes, beginner-friendly datasets, visual storytelling principles. Community upskilling as a form of advocacy.

CHAPTER 03 — DATA PLAYGROUND

ME,CHARTED

Decorative viz. Real vibes. Hover everything.

24H LOADOUT

How I spend a typical day (%)

CAFÉ ORDERS (YTD)

Field research, documented

INTEREST GRAPH

Click a node. Watch the psychic links light up.

DataAnimeZinesCafésTypeHokkaidoSQLSaiki KVizManga

CHAPTER 04 — SIDE QUESTS

Not all quests show up on a CV. Some of them have very good ties.

TiedTwice shop avatar

TiedTwice.pk

ACTIVE QUESTQuest: find the perfect tie. Status: ongoing.

thrifted ties & belts

I sell the sickest ties and belts you've ever seen.

Visit Shop →
Thrifted silk tie — common rarity
COMMON

People STILL ask me about this tie

Why I picked it:

SCOOBY DOOBY DOOOOOOOOOO

Vintage belt — rare rarity
RARE

THE BLING OMG

Why I picked it:

Belt wala showed me this and I knew he was the one

Loud pattern tie — legendary rarity
LEGENDARY

I WANTED TO KEEP THIS FOR MYSELF

Why I picked it:

Every techie needs a tie like this

CHAPTER 05 — OPEN CHANNEL

café_order.form — 注文