Omar Tawfik, standing in front of Boston rooftops

Omar
Tawfik

Hey, I’m Omar.

I’m a software engineer

I’m a software engineer, data scientist, data engineer, business analyst, AI engineer, BU alumnus, Questrom MSBA candidate, and your next hire.
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Reading
MS Business Analytics, BU Questrom
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BA Economics & Computer Science, Boston University
Seeking
Technology and data roles, 2027
Located
Boston · New York City

Work

Six roles, two countries

The PODS landing page — "Find your people. Do the thing." — beside the app's Discover screen
Boston

Founder & Full-Stack Engineer

PODS — Boston · Jan 2026–Present

  • Founded and led a student team building a campus platform for short-term, activity-based groups — grew to 50+ active users and reached the semifinals of an $80K venture competition.
  • Architected the full stack: REST APIs with token auth, a normalized SQL schema, and real-time notifications on AWS.
  • Built an agentic group-matching system with context and state management, replacing manual coordination.
50+
users
$80K
competition

My Story

Six cities, three continents

Three continents before I finished school. In order:

Tokyo Tower at night above Minato

01 / 06 · Japan

Tokyo

Born here. Left before I could walk.

Photo: David Kernan · CC BY 4.0

Projects

Built because I wanted them to exist

All my code on GitHub ↗github.com/otawfik

Deep Q-Learning for Risk

Java · Deep reinforcement learning

A two-person Java project with no ML frameworks: a dual-decoder deep Q-network scores every legal move in multi-agent Risk from 41 engineered features. Won 72% of head-to-head games over a 31-game evaluation and matched a 30-rollout MCTS agent with one forward pass.

72%
head-to-head wins
9/9
vs heuristic agent
41
features

PODS

BU Innovate grant

Python · Flask · React · SQL · AWS

A campus platform for short-term, activity-based groups — study sessions, workouts, pickup games. 50+ active users, semifinals of an $80K venture competition, and agentic group-matching in place of manual coordination.

50+
active users
$80K
competition

FootSnap

TypeScript · React Native / Expo · Vercel Edge · Python · OpenCV

A collectible card game on live football data: every player in Europe's top five leagues and the Champions League is a card rated from this season's stats. Forecasts come from a maximum-likelihood Poisson goals model, and a Monte Carlo simulator replays the season 3,000 times.

~3,000
live player cards
3,000
seasons simulated

Cosmic Explorer

JavaScript · React · Canvas · Linear algebra

An eight-planet arcade game where every frame is linear algebra — motion, orbits and collisions computed as explicit vector and matrix operations, with no game engine. Each mission runs on its planet's real physical constants.

8
mini-games
0
game engines

Fridge Vision

Python · YOLOv8 · scikit-learn · Flask

Photograph your fridge and get back what's inside, how fresh it is and what to cook. YOLOv8 finds the items, a freshness classifier I trained on 44 hand-built features scores each one (97.5% held-out), and TF-IDF retrieval matches recipes.

Image: Real output on a Wikimedia Commons photo by Candeadly (CC BY 4.0)

97.5%
freshness accuracy
1,200
training photos

PricePilot

Python · NumPy · SciPy · pandas · Flask

Retail price optimization end to end: per-SKU demand elasticities from log-log regression, then profit-optimal prices inside guardrails. On a simulated two-year panel of 43,800 transactions it lifts daily profit 24.6%, and the estimates recover the known ground truth.

+24.6%
profit uplift (sim.)
60
SKUs repriced

Billboard: Top 10 or Not?

Python · pandas · SciPy · MusicBrainz API · Jupyter

A team analysis of what gets a Hot 100 song into the Top 10: an 8-stage Python ETL fuzzy-joins the chart archive, lyrics and MusicBrainz into 5,342 songs. Artist history is the strongest predictor (5.8% → 18.5% Top 10 rate), and we caught a target leak.

5,342
songs
~99%
join accuracy
8
ETL stages

Uninutri

React · TypeScript · Vite · Gemini API

A nutrition tracker for BU students that logs meals against what the dining halls are actually serving. Staff post the day's menu from a portal, and Gemini estimates each dish's macros from its name and description.

More builds

Forecast Studio

Six forecasting models, naive baselines to Holt-Winters and ARIMA, compared under walk-forward backtests with 95% intervals.

Live demo ↗Source ↗

RAG-in-a-Box

A fully offline retrieval-augmented chatbot whose answers cite the exact source sections.

Live demo ↗Source ↗

LoRA Lab

LoRA from scratch in NumPy: a rank-8 adapter (9.6% of the parameters) on a frozen base model, A/B'd side by side.

Live demo ↗Source ↗

Agent Arena

A from-scratch multi-agent framework — planner, debaters, fact-checker and judge — streamed live to a dashboard.

Live demo ↗Source ↗

PromptForge

Version, test and A/B prompts like code, with six local scorers and a running leaderboard.

Live demo ↗Source ↗

All my code on GitHub ↗Every project above, plus coursework and experiments

Toolkit

What I reach for

Languages
PythonRSQLJavaScriptJavaHTML/CSSSTATA
Frameworks
PandasNumPyscikit-learnTensorFlowMatplotlibSeabornReactFlask
Developer tools
AWSGitDockerJupyterFigmaJIRANotion
Analytics
Power BITableauExcel (advanced)Google AnalyticsTime-series
Spoken
English — nativeFrench — fluentArabic — fluentSpanish — conversational
Coursework
Machine LearningEconometricsData Structures & AlgorithmsArtificial IntelligenceDatabases & SQLFinancial EconomicsSoftware Engineering

Elsewhere

Away from the screen

Omar playing a grand piano

Piano

The closest thing I have to a system clicking into place — structure underneath, room to move on top.

Close-up of a chess pawn wearing a crown, facing down the opposing pawns

Chess

The same appeal as the analytics work, stripped to its bones: incomplete information, a clock, and no one to blame.

Beat me if you can →
—
Blitz
—
Rapid
—
Bullet
Competition swimming pool with lane ropes and starting blocks

The water and the pitch

I swam competitively, then taught it — a hundred-odd lessons at Asphalt Green. Football is the other one, close enough that I built an analytics platform for it rather than just watching.

Contact

Open to technology and data roles starting 2027.

Always up for a conversation about football analytics, or about what actually happens to a model once someone has to act on it.

Omar Tawfik