Pythonscikit-learnMLflow
Telecom Churn Prediction
Production-grade telecom churn prediction system: a config-driven scikit-learn pipeline with SHAP explainability, MLflow experiment tracking and FastAPI serving, trained on…
Building reliable data & AI systems
Muhammad Farooq
Data Engineer · AI Engineer · Data Scientist
01 · About
From raw data to reliable, production-grade systems.
I’m Muhammad Farooq (also known as Muhammad Farooq Shafi), a data engineer and machine learning practitioner focused on building systems that hold up under real scrutiny — not just notebooks that ran once. My work spans the full data lifecycle: ETL pipelines with automated data-quality gates, dbt-modeled analytics warehouses backed by dozens of automated tests, and ML systems evaluated honestly against real baselines rather than a single flattering metric. I’ve built and deployed projects across intrusion detection, recommendation systems, NLP triage, demand forecasting, and computer vision — each one served through a real API or interface, versioned, and tested, not left as a one-off script. I write regularly about the engineering discipline behind trustworthy data work: honest evaluation, reproducible pipelines, and deployment done right.
Muhammad Farooq
Data Engineer · AI Engineer · Data Scientist
0
Projects shipped
0
Certifications
0
Roles & simulations
02 · Tech Stack
Tools I use to move data — and make it useful.
Data Engineering
Python
92%
SQL
90%
Apache Spark
78%
Apache Airflow
80%
Kafka
70%
dbt
82%
ETL / ELT
88%
Data Warehousing
85%
Cloud & Platforms
Snowflake
75%
Databricks
72%
Azure
76%
AWS
74%
GCP
68%
Docker
84%
Kubernetes
65%
Linux
80%
AI & Machine Learning
Machine Learning
88%
Deep Learning
75%
TensorFlow
72%
PyTorch
74%
Scikit-learn
90%
LLMs & RAG
78%
LangChain
70%
Generative AI
80%
Analytics & Tools
Pandas / NumPy
92%
Power BI
70%
Tableau
68%
Excel
85%
FastAPI
80%
Streamlit
78%
Git & GitHub
90%
OpenCV
65%
03 · Selected Work
All projects →
Projects built to run in production, not just in a notebook.
PythonSQLETL
Marketing Analytics Data Pipeline
An end-to-end marketing analytics data pipeline that ingests, transforms and models campaign data for reporting.
PythonRAGLLMs
Knowledge-Base Search (RAG)
A knowledge-base search system built with retrieval-augmented generation for accurate, grounded question answering.
PythonTime SeriesForecasting
Energy Demand Forecasting
A time-series forecasting system for energy demand, built for planning and load-balancing use cases.
PythonGraph AnalysisNetworkX
Organizational Network Analysis
Graph-based analysis of organizational networks to surface influence, collaboration and communication patterns.
Pythonscikit-learnMachine Learning
Fraud Detection System
A classical machine learning system for detecting fraudulent transactions with a focus on precision/recall trade-offs.
04 · Open Source
Building in public.
A live snapshot of my GitHub activity — commits, streaks and languages.
View GitHub profile →
05 · Experience
Where I've applied it.
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Apr 2025 – Aug 2025 · Remote
Machine Learning Engineer — CodeAlpha
Machine Learning Engineer (Internship) · CodeAlpha
Developed and implemented machine learning models for real-world applications using Python, TensorFlow and scikit-learn. Performed data preprocessing, feature selection and model tuning, and collaborated with cross-functional teams to integrate ML solutions into existing products.
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Jun 2025 – Aug 2025
Data Science Intern — Arch Technologies
Data Science Intern (Internship) · Arch Technologies
Assisted in data collection, cleaning and preprocessing to support machine learning projects. Developed and tested predictive models using Python and libraries including scikit-learn and pandas, and created data visualizations to communicate insights.
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May 2025 – Aug 2025 · Hybrid
Data Science Intern — Oasis Infobyte
Data Science Intern (Internship) · Oasis Infobyte
Supported data preprocessing, feature engineering and exploratory data analysis for ongoing machine learning projects, and assisted in building and evaluating predictive models with scikit-learn and pandas.
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Jun 2025 – Aug 2025 · Remote
British Airways — Data Science Job Simulation
Data Science Job Simulation (Forage) · British Airways
Scraped and analysed customer review data to uncover findings, and built a predictive model to understand the factors that influence buying behaviour.
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Jan 2025 – Jul 2025 · Remote
BCG X — Data Science Job Simulation
Data Science Job Simulation (Forage) · BCG X
Completed a customer churn analysis simulation, conducting data analysis in Python (pandas, NumPy), engineering and optimizing a random forest model that achieved a 50% recall rate in predicting churn, and delivering an executive summary of findings.
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Apr 2025 – Aug 2025
Commonwealth Bank — Introduction to Data Science Job Simulation
Data Science Job Simulation (Forage) · Commonwealth Bank
Built data engineering pipelines to aggregate and extract insights from datasets, applied anonymization for data-privacy compliance, and proposed data analysis approaches for well-structured, efficient databases.
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Oct 2024 – Jul 2025 · Remote
Deloitte Australia — Data Analytics Job Simulation
Data Analytics Job Simulation (Forage) · Deloitte
Completed a job simulation involving data analysis and forensic technology, created a data dashboard using Tableau, and used Excel to classify data and draw business conclusions.
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Feb 2025 – Jul 2025
Quantium — Data Analytics Job Simulation
Data Analytics Job Simulation (Forage) · Quantium
Developed expertise in data preparation and customer analytics using transaction datasets, identified benchmark stores for uplift testing, and created reports for informed, evidence-based strategic decisions.
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Jul 2025 · Remote
Lloyds Banking Group — Data Science Job Simulation
Data Science Job Simulation (Forage) · Lloyds Banking Group
Completed a Forage job simulation for Lloyds Banking Group's data science team.
06 · Education
Foundations.
Riphah International University
Bachelor's degree, Artificial Intelligence
Jul 2023 – May 2027
Focused on the design, development and deployment of AI-driven systems. Coursework and projects covered machine learning, deep learning, computer vision, natural language processing and robotics, with hands-on expertise in Python, TensorFlow and PyTorch.
Virtual University of Pakistan (VU)
Associate's degree, Data Science
Apr 2024 – Mar 2026
Developed a strong foundation in data analysis, statistics, programming and machine learning.
Allama Iqbal Open University (AIOU)
Associate's Degree, Business Administration and Management
Jun 2025 – Jun 2026
Participated in business case studies, management discussions and leadership development activities focused on strategy, marketing and organizational management.
07 · Certificates
Google
Always learning, always shipping.
IBM Generative AI Engineering
IBM · Credential ID MFXW3LL9UI6G
Introduction to AI
Google · Jun 2025
IBM AI Engineering Professional Certificate (V3)
Coursera · Jun 2025
Data Analysis with Python
Coursera
IBM Deep Learning with PyTorch, Keras and TensorFlow
IBM · Jun 2025 · Credential ID FVMJDQSAUDL6
AI for Beginners
HP LIFE · Feb 2025
Data Science & Analytics
HP LIFE · Mar 2025
Google AI Essentials
Hands-On Python Machine Learning with Real World Projects
Udemy
Effective Presentation
HP LIFE · Feb 2025
Effective Leadership
HP LIFE · Feb 2025
Master Class on Data Science using Python A-Z for ML
Udemy · Nov 2024
AI Essentials: Introduction to Artificial Intelligence
Udemy · Nov 2024
Data Structures Using Python
Udemy
08 · Services
How I can help.
Data Pipeline & ETL/ELT Engineering
Design and build reliable, monitored pipelines that move data from source systems into warehouses and marts, ready for analytics.
Cloud Data Warehousing
Model and deploy star-schema warehouses on Snowflake, Databricks or DuckDB with automated data-quality testing.
Machine Learning & MLOps
Train, explain and serve ML models with MLflow tracking and FastAPI/Docker deployment.
Analytics & Dashboards
Turn raw data into decision-ready dashboards with Streamlit, Power BI or Tableau.
11 · Writing
All posts →
Notes on data engineering & AI.
Naive Bayesian Classifiers: How They Actually Work
Naive Bayesian classifiers are built on an assumption that’s almost always technically wrong. Here’s why it works anyway, and when it’s the right tool.
Read more →
Support Vector Machines Explained: The Margin That Matters
Plenty of lines can separate two classes of points. A support vector machine specifically finds the one with the widest possible margin. Here’s how and why.
Read more →
Gradient Boosting Explained: How It Actually Works
Gradient boosting gets described often and explained rarely. Here’s how it actually works, step by step, and the hyperparameters that genuinely matter.
Read more →
12 · FAQ
Good questions.
What kind of projects do you take on?
I work on data pipelines, warehouse modeling, ETL/ELT, and applied ML/AI projects — from a single dashboard to a full production pipeline.
Are you available for freelance or full-time roles?
Yes — update this answer with your current availability.
What tools do you use most?
Python, SQL, dbt, Airflow, Docker, and cloud platforms including AWS, Azure and GCP, alongside scikit-learn/TensorFlow/PyTorch for ML work.
13 · Contact
Have a data problem worth solving?
Send a message and I'll get back to you soon — or reach out directly: