🚀 Building intelligent AI systems that turn complex data into real business impact

I’m a Lead AI Engineer and Data Scientist with 10+ years of experience building production-grade AI systems across fintech, banking, telecom, retail, and enterprise domains.

I specialize in designing and deploying end-to-end intelligent systems — from data pipelines to machine learning models to LLM-powered applications — that are scalable, explainable, and deliver real-world impact.

• 🤖 Generative AI & LLM Systems (OpenAI, Azure OpenAI, AI Assistants)
• 📊 Machine Learning & Predictive Modeling (Churn, Risk, Forecasting)
• ⏳ Advanced Modeling (Survival Models, Time Series, XGBoost, LightGBM)
• 🔍 NLP, OCR & Computer Vision (Document AI, Multilingual OCR)
• ☁️ Cloud AI Systems (Azure, GCP, AWS, Databricks, Vertex AI)
• ⚙️ ML Engineering (Pipelines, APIs, CI/CD, Production Deployment)

• 🧠 Focus on systems thinking (not just models)
• 📈 Strong emphasis on business impact & ROI
• 🔍 Built-in explainability (SHAP), calibration, and drift monitoring (PSI)
• 🔗 Experience with hybrid AI systems (ML + rules + heuristics)
• 🚀 Proven track record of production-grade deployments

✔ Building LLM-powered systems & AI assistants
✔ Designing scalable ML pipelines (data → model → API → production)
✔ Developing risk, forecasting & decision intelligence systems
✔ Architecting cloud-native AI solutions
✔ Solving real-world fintech & enterprise problems

• 🔹 LLM Analytics Assistant → Natural language → SQL engine for business users

• 🔹 AI Document Intelligence System (OCR + LLM) → Structured data extraction with anti-hallucination validation

Extract structured financial data from invoices using LLMs with anti-hallucination guarantees

🧠 Problem Traditional OCR systems produce unreliable outputs and require manual validation.

💡 Solution LLM-based extraction pipeline with confidence scoring and validation.

📊 Impact

• Reduced manual processing effort
• Improved extraction reliability
• Enabled scalable document automation

⚡ Tech: OpenAI, FastAPI, Gradio, OCR Pipeline

Predict salary stability across future months using survival modeling

🧠 Problem Lending systems lack visibility into future income stability.

💡 Solution Multi-horizon survival model with explainability and real-time scoring.

📊 Impact

• Improved risk-based decision making
• Enabled explainable credit scoring
• Enhanced prediction reliability

⚡ Tech: LightGBM, SHAP, FastAPI, Survival Modeling

Match and validate financial transactions across multiple systems

🧠 Problem Manual reconciliation is slow and error-prone.

💡 Solution Automated reconciliation engine with multi-step matching logic.

📊 Impact

• Reduced reconciliation effort
• Improved financial accuracy
• Automated reporting workflows

⚡ Tech: Python, PostgreSQL, Pandas

Real-time customer identity matching using ML + rules

🧠 Problem Customer data is fragmented across systems.

💡 Solution Hybrid ML + rule-based scoring with explainability.

📊 Impact

• Improved matching accuracy
• Reduced duplicate records
• Enabled real-time resolution

⚡ Tech: Scikit-learn, FastAPI, Feature Engineering

• Machine Learning: Scikit-learn, XGBoost, LightGBM, Random Forest, SVM
• Deep Learning: TensorFlow, PyTorch, Keras, LSTMs, CNNs, BERT
• Generative AI / LLMs: OpenAI, Azure OpenAI, Prompt Engineering, LLM Agents
• NLP & Document AI: Text Extraction, OCR, Multilingual NLP (English & Urdu)
• Computer Vision: Object Detection, Keypoint Detection, Image Processing

• Microsoft Azure: Azure Machine Learning, Azure OpenAI, Cognitive Services, Azure Databricks, Synapse Analytics, Data Factory, Blob Storage
• Google Cloud Platform (GCP): Vertex AI, BigQuery, Dataflow, Dataproc
• AWS: SageMaker, Lambda, EC2, S3, RDS

• PySpark • Apache Spark • Dataiku DSS • Talend
• SQL • PostgreSQL • BigQuery • Snowflake
• Data Pipelines • ETL • Feature Engineering

• FastAPI • Flask • Django REST Framework
• REST APIs • Microservices • Model Deployment
• Docker • CI/CD Pipelines • Azure DevOps

• Pandas • NumPy
• Power BI • Tableau • Plotly • Matplotlib • Seaborn

• Python • PySpark • C# • Java

• 💰 Saved $2M+ via fraud detection
• 📉 Reduced loan defaults by 12%
• ⚡ Improved reconciliation efficiency by 70%
• 📊 Increased marketing ROI by 25%

flowchart LR
A[Raw Data] --> B[Data Engineering]
B --> C[Feature Engineering]
C --> D[ML / LLM Models]
D --> E[APIs & Services]
E --> F[Business Applications]

• 🟦 Microsoft Certified: Azure Data Scientist
• 🟦 Microsoft Certified: Azure AI Engineer
• 🟥 Google Cloud AI & ML Certifications

"AI is not just about models — it's about building intelligent systems that create real-world impact."

🚀 Always building. Always learning.