Yassa Fareed
@yassafareed
I build AI and data systems that automate workflows and turn raw data into insights.
PakistanWhat I'm looking for
I'm building AI and data systems at tappengine, following software engineering work at Surmount, where I helped automate broker accounts with data-driven strategies.
At SimpliFi, I worked across infrastructure and data, using Python, Kubernetes, Terraform, Docker, Trino, Airflow, Grafana, and data warehousing tools to support scalable pipelines and monitoring.
At SnappRetail, I built anomaly-detection and credit-scoring solutions from retailer POS data, deploying daily inference workflows on AWS EC2 and developing Flask APIs for training, preprocessing, and scoring.
My earlier work spans computer vision, IoT, forecasting, web scraping, and backend APIs. I've deployed object-detection models to Raspberry Pi and Google Coral Edge TPU, built Forex prediction models, and continue to pursue practical technology that creates impactful solutions.
Experience
Work history, roles, and key accomplishments
AI Engineer at tappengine, focusing on AI and data systems.
Worked as Software Engineer at Surmount.
Worked as Software Engineer - Infrastructure & Data at SimpliFi.
Worked on:
- Anomaly Detection: Preprocessed and cleaned raw retailer POS data to represent individual transactions, performed feature engineering, and trained unsupervised machine learning models to detect anomalous transactions. Used AWS EC2 for model training, and scheduled daily inference using Linux CLI (crontab) to automatically email transaction status and relevant store data. Developed Fla
- Worked as a Python Django Backend Developer and Data Scientist.
- Developed time series models for Forex prediction using recurrent neural networks (RNNs) to predict the probability of price increase or decrease based on trends from the past 14 days; deployed the model on an AWS EC2 instance.
- Conducted web scraping on Reddit to analyze Forex ticker sentiment by tracking mention counts; process
- Worked on a Computer Vision & IoT-based Smart City Safety Surveillance Module, later continued as our Final Year Project for an additional year.
- Designed a mechanism to address data drift that occurs when deploying object detection models.
- Utilized two devices: Google Coral Edge TPU and Raspberry Pi 4.
- Collected image data for fire, mask/no-mask, and weapons from sources like YouTube, Goog
Remote internship.
Did 5 "Tasks" like exploratory data analysis and model predictions.
Tasks: https://github.com/YassaFareed/The-Sparks-Foundation-Tasks
Education
Degrees, certifications, and relevant coursework
National University of Computer and Emerging Sciences
Bachelor's degree, Computer Science
2018 - 2022
Competitions:
DevDay 2021 Data Science competition winner
DevDay 2022 Data Science competition winner
PIAIC
AI & ML
2019 - 2020
AI Specialization (4-Quarter Program | 4 hours/week)
Completed a comprehensive AI course covering Python, Machine Learning, NLP, CNNs, and cloud deployment. Key topics and skills included:
- Python for Machine Learning: Utilized libraries such as NumPy, Pandas, and Scikit-learn for data processing and model building.
- Model Training & Optimization: Built and optimized Classification and Regressi
Whales College
GCE A' Levels, Science
2016 - 2018
Karachi Public School
GCE O' Levels
Tech stack
Software and tools used professionally
Availability
Location
PakistanAuthorized to work in
Portfolio
github.com/YassaFareedSalary expectations
Job categories
Skills
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