Biswajit P.

Background

About Biswajit P.

I turn complex data challenges into scalable, high-performance AI/ML and data engineering solutions. With hands-on experience in building ETL pipelines, transforming unstructured datasets, and supporting machine learning models in production, I bridge the gap between data engineering and applied AI. My expertise spans Python, SQL, and Azure, with strong foundations in NLP, Generative AI, and model optimization. I focus on delivering solutions that are technically sound and business-driven, empowering organizations to make smarter, faster decisions. I design cloud-native data pipelines, automate feature engineering, deploy machine learning models, and enable real-time analytics. Whether it’s backend optimization, AI model deployment, or orchestrating large-scale data workflows, I deliver measurable impact. CAREER HIGHLIGHTS Supported an AI-powered customer churn prediction project, achieving ~87% accuracy using structured and unstructured customer data. Designed and implemented ETL pipelines that prepared 50K+ records for ML readiness, improving data consistency by ~25%. Processed and analyzed 10K+ chat transcripts and 100+ call recordings for NLP-based insights and acoustic feature extraction. Deployed a prototype ML model on Azure cloud for live demonstration to business stakeholders. Developed dynamic Power BI dashboards, reducing reporting efforts by ~40% and enabling data-driven decision-making. AREAS OF EXPERTISE AI/ML & GenAI (NLP, Feature Engineering, RAG, Transformers, Prompt Engineering) Data Engineering & ETL Pipelines (Python, SQL, PySpark, Airflow, Pandas) Model Deployment & Optimization (Azure, Docker, REST APIs) Cloud & MLOps (Azure, Git, CI/CD) Data Visualization & Reporting (Power BI, Data Warehousing) TECHNICAL SKILLS Programming Languages & Libraries: Python, Java, SQL, Pandas, NumPy, scikit-learn, XGBoost, Keras, TensorFlow AI/ML & GenAI: NLP, Transformers, Retrieval-Augmented Generation (RAG), Prompt Engineering, Feature Engineering, Model Evaluation Data Engineering: ETL, Data Modeling, Data Warehousing, Data Pipelines, PySpark, Airflow Cloud & Tools: Microsoft Azure, Docker, Git, GitHub, Maven, REST APIs ML Engineering: Model Deployment, Model Optimization, ML Prototyping on Azure Data Visualization & Reporting: Power BI, Dynamic Dashboards, Automated Reporting CERTIFICATIONS Machine Learning Specialization – Stanford Online Microsoft Certified: Azure AI Fundamentals Microsoft Certified: Azure Fundamentals