Muhammad Noman B.
Python Data Scientist, ML & Big Data Engineer, Generative AI -LLM, API
🔴 Data Scientist & AI Engineer with 5+ years in tech, skilled in Generative AI (LLMs, RAG, AI Agents, LangChain, XAI, Vector DBs), Machine Learning -MLOps, Big Data Engineering (Hadoop, Spark, Kafka, Hive, Cloudera, Databricks, Snowflake), Cloud (AWS, GCP, Azure), and BI (Power BI, Tableau, IBM Cognos Analytics) I help enterprises transform raw data into scalable AI/ML solutions that cut costs, boost efficiency, and drive measurable ROI. 💼 Work: ✅ AI Agents & Chatbots: Built IBM Watson + LLM (LangChain, RAG, XAI) chatbot handling 5,000+ monthly queries, cutting response time by 40% and boosting CSAT by 18% ✅ Fraud Detection Models: Developed an ML pipeline improving transaction monitoring by 20% accuracy and reducing false positives by 15% ✅ OCR & Automation: Engineered OCR workflow with Python/OpenCV, integrated into Temenos T24, reducing manual data entry by 60% ✅ Data Pipelines: Automated ETL (DB2 → Hive → SQL Server → Power BI Server) via PySpark/Scala + Cron, reducing runtimes by 30% and ensuring reliability with log monitoring ✅ Big Data Engineering: Managed 12-node Cloudera clusters (100+ TB) with 99.9% uptime, optimizing Spark + Hive workloads for faster queries ✅ BI Dashboards: Designed 30+ dashboards in Power BI, Tableau, Qlik & IBM Cognos, deployed for 1,000+ enterprise users across Risk, Compliance & Finance ✅ Streaming Pipelines: Built Kafka + Spark streaming systems for real-time analytics, processing 2M+ daily transactions ✅ Regulatory Reporting: Automated SBP compliance reports (Python + SQL chaining), cutting manual effort by 70% ✅ RPA Bots: Built a Selenium-based compliance bot, saving 50+ hours/month in analyst workload ✅ Data Warehousing: Migrated 50+ TB structured/unstructured data on Cloudera stack (Hive, HDFS, Impala), cutting storage costs by 20% 💻 Skills: ☑ Languages: Python, R, Scala, SQL, Bash ☑ Generative AI: LLMs (GPT, LLaMA, Claude), LLM fine-tuning (LoRA, PEFT), RAG pipelines, LangChain, LlamaIndex, AI Agents, Vector Databases (Pinecone, Weaviate, FAISS, Milvus, ChromaDB), Prompt Engineering, Chatbots, Multi-Modal AI, Knowledge Graphs, Guardrails, XAI (SHAP, LIME) ☑ Big Data & Cloud: Cloudera, Hadoop (HDFS, MapReduce, YARN), Spark (PySpark/Scala, MLlib, Streaming), Kafka, Flink, Hive, Pig, Impala, Storm, Sqoop, Oozie, NiFi, Zookeeper, Databricks, Snowflake, Delta Lake, Data Warehouse Architecture, Presto, AWS (SageMaker, EMR, S3, Lambda, Redshift), GCP (BigQuery, Vertex AI), Azure (Synapse, ML, OpenAI) ☑ ETL & Data Engineering: Airflow, dbt, Cron, Pandas, NumPy, Spark SQL, Data Wrangling, APIs, Automation, ETL pipelines, OpenCV, BeautifulSoup, Scrapy ☑ Databases: SQL Server, MySQL, PostgreSQL, IBM DB2, MongoDB, Hive, Cassandra, Redis, Elasticsearch ☑ Machine Learning & Data Science: Predictive analytics (Deposit Prediction, Fraud Detection), NLP, Computer Vision, OCR, Supervised/Unsupervised Learning, Reinforcement Learning, Deep Learning (CNNs, RNNs, Transformers), scikit-learn, TensorFlow, Keras, PyTorch, XGBoost, LightGBM, CatBoost, Hugging Face, AutoML, MLOps (MLflow, Kubeflow, DVC, Airflow ☑ Business Intelligence & Visualization: Power BI, Tableau, Looker, Qlik, IBM Cognos Analytics, Excel, Matplotlib, Seaborn, Plotly, PBI Report Server Configuration ☑ Development (Backend & Full-Stack): Python (APIs, automation, ETL, backend), Django, Flask, FastAPI, Streamlit, Node.js, React, WordPress (Elementor), Odoo ERP, AI SaaS apps ☑ Automation: RPA bots (Selenium), Web Scraping, ETL Workflow Automation ☑ DevOps & Tools: Git, Gitlab, Docker, Kubernetes, CI/CD pipelines, Jupyter, PyCharm, Anaconda Distribution 🌎 Trusted by clients in banking, fintech, e-commerce, and enterprise systems for writing clean, scalable, and production-ready code. 📩 Not sure where to start? Share your challenge with me, and I’ll map out a step-by-step AI/data strategy - no fluff, just actionable insights that you can apply right away.
Earnings and projects
An estimate from an earlier read
Billed in all: $1,039$1k
Across 14 contracts
Earnings, last 30 days
No data since Nov 5, 2026.