Hi, I'm Bilal Momin

Data Science Consultant

I'm a Data Scientist and AI Consultant with 4+ years of experience in building scalable machine learning systems, intelligent data pipelines, and LLM-powered applications. I specialize in creating end-to-end GenAI solutions—from real-time web crawling and feature engineering to deploying LLM-based tools like resume builders, Q&A bots, and document intelligence systems.

I’ve worked across industries including finance, education, and media tech—combining my skills in Python, cloud (GCP, AWS), LangChain, Kafka, and ML frameworks to deliver impactful, production-ready tools. Passionate about solving real-world problems with AI, I focus on building solutions that are scalable, smart, and user-friendly.

View Projects Contact Me
Bilal Ayyas Momin

Technical Skills

Data Engineering

Python SQL Apache Spark PySpark Airflow Kafka BigQuery Google Cloud Platform AWS ETL Pipelines Data Warehousing Docker Kubernetes MongoDB PostgreSQL

AI & ML

Machine Learning Deep Learning TensorFlow PyTorch Scikit-learn NLP LLMs LangGraph RAG (Retrieval-Augmented Generation) LangChain Prompt Engineering OpenAI Transformers Fine-tuning

Cloud & DevOps

Google Cloud Platform (GCP) AWS Cloud Functions Cloud Run Docker Kubernetes CI/CD GitHub Actions Cloud Storage Compute Engine Fargate Cloud Monitoring

Professional Journey

Freelance Data Science Consultant

Self-employed

June 2023 - Present

Designed and delivered AI-powered tools and applications using LLMs, LangChain, and cloud technologies. Focused on creating scalable, real-time NLP systems for document intelligence, resume automation, and financial analysis.

Key Achievements:
  • Built an LLM-based Document QA system using LangChain and ChromaDB for natural language interaction across PDF, CSV, and XLSX files
  • Developed a portfolio Q&A assistant allowing users to query financial data and stock performance using RAG pipelines and OpenAI
  • Created an LLM-powered resume generator that converts plain text input into polished, personalized resumes
  • Developed a chatbot for querying structured financial datasets with high retrieval accuracy using custom embeddings
  • Handled all aspects from ingestion and preprocessing to embedding storage, vector search, and LLM orchestration

Data Engineer

Admazes Limited, Hong Kong

December 2021 - Present

Led the development of scalable data pipelines, automated data ingestion systems, and ML classification tools across high-volume data sources. Focused on building reliable infrastructure and delivering actionable business insights through robust engineering and modeling practices.

Key Achievements:
  • Developed and maintained data crawlers for Quora, Reddit, Twitter, LinkedIn, and TOR—processing millions of records with real-time error handling and deduplication
  • Engineered ETL pipelines that handled 100M+ monthly Google SERP records for trend forecasting and demographic analysis using clustering and regression models
  • Built a topic classification engine using ML models (e.g., fine-tuned BERT) for organizing search queries into categories with high accuracy
  • Performed complex data wrangling, cleaning, and transformation across diverse data formats (JSON, text, tabular, unstructured)
  • Managed API deployments and database hosting on Google Cloud using Docker, Kubernetes, and Compute Engine

Python Developer

Codemarket, California

December 2020 - February 2021

Contributed to backend development and cloud-based deployments of modern web applications, supporting real-time API workflows and data integrations.

Key Achievements:
  • Built RESTful and GraphQL APIs using Python and MongoDB for high-performance frontend consumption
  • Deployed scalable microservices using AWS Lambda, Fargate, and ECR within a containerized architecture
  • Collaborated across teams and managed multiple GitHub repositories simultaneously
  • Supported frontend-backend integration using React and ensured consistent data flow between services

Featured Projects

University Q&A System with LLM & RAG

University Q&A System with LLM & RAG

Built an LLM-powered Retrieval-Augmented Generation (RAG) system that allows users to ask natural language questions about 100+ universities. Integrated data from Quora and Reddit using scalable crawlers. Designed chunking, metadata tagging, and vector search using LangChain and OpenAI to return accurate, context-aware responses.

LangChain RAG OpenAI ChromaDB Python MongoDB Vector Search
View Project
Search Query Trend Prediction Platform

Search Query Trend Prediction Platform

Engineered a data pipeline to process 100M+ monthly Google SERP records and forecast keyword trends using clustering and regression models. Handled large-scale data ingestion, transformation, and analytics for business insights.

ETL BigQuery Dataflow ML Python Scikit-learn GCP
View Project
ML-Based Topic Categorization Engine

ML-Based Topic Categorization Engine

Created an end-to-end machine learning pipeline to classify search queries into relevant marketing categories. Implemented text preprocessing, model training using fine-tuned BERT, and deployed real-time prediction APIs on Google Cloud. Used for search analytics and content tagging.

ML Text Classification BERT Python Google Cloud APIs
View Project
View All Projects