Applied AI engineer with a data science and analytics background, 4+ years of Python/SQL experience, and hands-on work building LLM applications, AI agents, and agentic workflows.

I build practical systems with OpenAI API, Anthropic API, Gemini API, Google ADK, RAG, tool calling, structured outputs, evals, Langfuse tracing, FastAPI, PostgreSQL, Docker, and cloud deployment patterns.

I hold a Master of Data Science from UBC and a BSc in Computer Science from AIUB (CGPA: 3.91/4.0). My public case studies include Maintenance-Eye, a real-time multimodal maintenance copilot built with Google ADK, Gemini Live API, FastAPI, Firestore, and Cloud Run.

Currently, I’m a Data & Applied AI Analyst at BC Rapid Transit Company where I build incident, KPI, maintenance, and asset-performance data workflows while mapping operational workflows into AI-ready use cases for decision support and diagnostics. GovIntel is my federal-procurement RAG project, built around USAspending ingestion, hybrid retrieval, SQL analytics, citation validation, FastAPI, and Streamlit.

What I Build

  • Applied AI systems — multimodal agents, RAG workflows, tool use, and human-in-the-loop safeguards
  • Python backends and data workflows — FastAPI services, ETL pipelines, structured analytics, and data modeling
  • Operational AI systems — systems shaped by real maintenance, reporting, and decision-support workflows

Professional Experience

BC Rapid Transit Company — Data & Applied AI Analyst

Dec 2024 - Present | Burnaby, BC

  • Build Python and SQL pipelines that consolidate incident, KPI, maintenance, asset-performance, and operational records into reliability-analysis datasets for reporting, natural-language querying, and AI-assisted decision support.
  • Translate maintenance and reliability workflows into AI-ready use cases across triage support, asset-context retrieval, recurring-failure investigation, KPI interpretation, and human-reviewed recommendations.
  • Prototype and support Microsoft/Azure automation workflows using Azure OpenAI, Azure AI Foundry, Copilot Studio, Power Platform, and tool-based interfaces for source-grounded operational analysis.
  • Improved recurring asset-performance validation and reporting workflows, saving 30-40 minutes per day while increasing consistency of maintenance review processes.

Brain Station 23 — Data Scientist, Financial Analytics & AI Workflows

Aug 2023 - Nov 2024 | Dhaka, Bangladesh / Remote

  • Built SQL, Python, and Power BI workflows for financial metrics, trend analysis, data consistency checks, recurring business reporting, and stakeholder-facing dashboards across multiple source systems.
  • Improved reporting efficiency by 21%, data consistency by 17%, and query performance by 26% through SQL optimization, ETL workflows, indexing, partitioning, Python preprocessing, and validation checks.
  • Created repeatable reporting and analysis workflows using SQL window functions, stored procedures, metric definitions, and data-quality checks to reduce manual review and improve analytical trust.
  • Contributed to financial analytics and document-intelligence workflows using Vertex AI, Cloud Functions, BigQuery, Python, SQL, and Power BI.

Statistics Canada — Data Scientist (Capstone)

Apr 2023 - Jul 2023 | Ottawa, ON

  • Implemented clustering algorithms (K-means, hierarchical) to segment the Proximity Measure Database for urban planning
  • Conducted data profiling, exploration, and outlier detection in R
  • Delivered actionable insights through cluster profiling for urban development policy recommendations

Softology IT — Co-Founder

Sep 2021 - Aug 2022 | Dhaka, Bangladesh

  • Co-founded a software development firm delivering Android apps, e-commerce solutions, and UI/UX design
  • Managed end-to-end project delivery across multiple concurrent client engagements

Selected Projects

Maintenance-Eye — Applied AI Project

2026 | Public project

  • Built and deployed a real-time multimodal maintenance copilot using Google ADK, Gemini 2.5 Flash Live API, FastAPI, Firestore, and Cloud Run
  • Implemented tool-using workflows for asset lookup, knowledge retrieval, work-order actions, and human-in-the-loop confirmation
  • Added deployment and reliability support with Terraform, Docker, GitHub Actions, and a multi-layer test suite

GovIntel — Federal Procurement Intelligence RAG System

2026 | Public project

  • Built a local-first procurement intelligence RAG system over USAspending awards
  • Implemented async ingestion, PostgreSQL persistence, Chroma indexing, BM25/vector retrieval, hybrid deduplication, cross-encoder reranking, SQL spend analytics, and fail-closed citation validation
  • Added a FastAPI analysis endpoint, Streamlit UI, Docker Compose workflow, CI, and automated tests

Education

University of British Columbia — Master of Data Science (Sep 2022 - Jun 2023)

American International University-Bangladesh — BSc in Computer Science & Engineering, CGPA: 3.91/4.0 (Jan 2018 - Sep 2021)

Certifications

Skills

AI Engineering and LLM Systems: Azure OpenAI, Azure AI Foundry, Anthropic API, Google Vertex AI, Gemini API, Google ADK, LangChain, LangGraph, LlamaIndex, LLM applications, AI agents, agentic workflows, RAG, tool calling, structured outputs, source grounding, human-in-the-loop workflows, prompt engineering

Automation, Evals, and Observability: AI automation, workflow automation, Copilot Studio, Power Platform, MCP, Microsoft Fabric, RAGAS, retrieval evals, citation validation, Langfuse tracing, logging, monitoring views, UAT support, technical documentation

Backend, Data, and APIs: Python, SQL, FastAPI, REST APIs, WebSockets, PostgreSQL, BigQuery, SQLAlchemy, Pydantic, pandas, ETL pipelines, data-quality checks, data modeling

Cloud, Delivery, and Testing: Cloud Run, Cloud Functions, Firestore, Docker, Docker Compose, GitHub Actions, pytest, Playwright, Streamlit, Terraform

Analytics and ML Foundation: Power BI, Tableau, scikit-learn, TensorFlow, R, clustering, classification, reliability analytics, KPI analytics, financial analytics