AI Engineer with 3+ years in Machine Learning, Cloud, and Data Science
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Assessing your cultural and operational fit
First Class Honours Data Science graduate with a track record of delivering production-ready analytics solutions. I specialize in building ML systems that scale (Azure, GCP), creating dashboards that inform decisions (Power BI, Tableau), and translating complex financial data into clear insights.
National School of Business Management (NSBM)
BSc (Honours) in Data Science · Data Science
August 1, 2022 – June 30, 2025
Mahinda Rajapaksha College
GCE Advanced Level · Physical Science Stream - Mathematics
N/A – May 31, 2020
Codebell PVT LTD
AI Engineer
February 1, 2025 – February 1, 2026
Beliatta, Hambantota District, Sri Lanka
Freelance
ML Engineer & Data Analyst
July 1, 2023 – February 1, 2025
India
LB Finance PLC
Customer Relations Officer
December 1, 2021 – April 1, 2022
Sri Jayewardenepura Kotte, Western Province, Sri Lanka
Multi-Agent Customer Retention System - Azure (Agentic AI & MLOps)
June 24, 2026 – Present
• Built autonomous AI system preventing customer churn using multi-agent architecture that correlates structured billing data with unstructured complaint logs, calculating dynamic churn risk scores for real-time retention decisions • Deployed production-ready FastAPI microservice on Azure with Vector RAG, achieving sub-second inference for automated offer negotiation based on customer value and sentiment analysis • Tools Used: Python, LangGraph, Google Gemini Flash, Azure Cosmos DB, Azure Blob Storage, FastAPI, Docker
View ProjectReal-Time NBO Engine on Azure Databricks (ML at Scale & Serverless)
June 24, 2026 – Present
• Architected serverless inference layer using Azure Functions and Blob Storage with global in-memory caching, achieving sub-100ms execution latency through optimized data serialization and cost-efficient auto-scaling architecture • Developed production-grade Next Best Offer engine utilizing Collaborative Filtering (ALS) on Azure Databricks with Apache Spark for distributed model training, enabling personalized product recommendations at enterprise scale • Tools Used: Azure Databricks, Apache Spark, Python, ALS Algorithm, Azure Functions, Azure Blob Storage, Streamlit
View ProjectAI Portfolio Intelligence Platform (Financial Analytics)
June 24, 2026 – Present
• Architected automated Financial Analysis Engine using LangGraph and Google Gemini with ensemble forecasting (Meta Prophet + Linear Regression), generating risk metrics (Sharpe Ratio, VaR) for 10+ assets while reducing data costs by 90% • Deployed production-ready Streamlit application via Docker for reproducible financial modeling across environments • Tools Used: Python, Meta Prophet, LangGraph, Google Gemini API, Docker, Streamlit.
View ProjectE-Commerce Customer Intelligence Platform - Azure (MLOps & Business Intelligence)
June 24, 2026 – Present
• Architected serverless Medallion Architecture (Bronze → Silver → Gold) on Azure Databricks processing 100k+ e-commerce orders, achieving cost optimization through PySpark optimization and Delta Lake ACID transactions • Delivered demand forecasting model (R2 0.36) and ALS-based recommendation engine after strategic pivot from churn prediction, deploying MLflow-tracked models with Docker and creating Power BI "Whale Detector" dashboard identifying high-value at-risk customers • Tools Used: Azure Databricks, PySpark, Delta Lake, Spark MLlib, XGBoost, MLflow, Power BI, Docker, Azure Data Factory
View ProjectHybrid Credit Risk Engine & Financial Explainability (Risk & Operations)
June 24, 2026 – Present
• Engineered credit scoring system processing 2.2M+ loan records with Polars streaming, reducing memory overhead by 87% (8GB to <1GB) and achieving 71% AUC with 30.5 KS statistic • Calibrated LightGBM model to FICO-style scores (300-850) for regulatory compliance, integrating Llama 3.2 for natural language explanations of loan decisions • Tools Used: Python, LightGBM, Polars, Llama 3.2, Streamlit, Scorecardpy
View ProjectGoogle Business Intelligence Professional Certificate
June 1, 2026 – Present
Microsoft Power BI Data Analyst Professional Certificate
Microsoft
June 1, 2026 – Present
Machine Learning Specialization
Stanford University
June 1, 2026 – Present
MLOps Specialization
Duke University
June 1, 2026 – Present
Advanced Machine Learning on Google Cloud Specialization
June 1, 2026 – Present
Azure Machine Learning Operations (MLOps) Engineer Associate (AI-300) Certification
Microsoft
June 1, 2026 – Present
Microsoft Azure Data Scientist Associate (DP-100) Certification
Microsoft
June 1, 2026 – Present
Meta Data Analyst Professional Certificate
Meta
June 1, 2026 – Present
Google Advanced Data Analytics Professional Certificate
June 1, 2026 – Present
Deep Learning Specialization
DeepLearning.AI
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, spanning customer retention, financial analytics, e-commerce, and credit risk, indicates a broad interest and adaptability to various business domains. Their involvement in data science competitions and research publications suggests a proactive and continuous learning mindset. The blend of academic achievements and practical project delivery, especially in cutting-edge AI, aligns well with an innovative and growth-oriented culture.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving abilities and stakeholder engagement, as evidenced by their customer relations experience and cross-functional collaboration in project delivery. Their freelance work indicates adaptability and client-facing skills. The focus on ethical AI and bias mitigation in their professional experience aligns with responsible AI development practices.