About Me
I'm a Data Science Lead at Gildan, where I lead a team turning data into the AI and decision systems behind a global manufacturer's operations, spanning demand forecasting, factory-floor optimization, and the enterprise AI agents that put those insights in people's hands.
What started as an engineering curiosity about how complex systems work has grown into a career focused on turning messy, real-world data into tools people can actually rely on. Over the years I've worked across telecom, agriculture, and manufacturing, on everything from satellite imagery and climate models to factory-floor sensors, using classical machine learning, deep learning, optimization, and modern AI.
Today my focus is the generative-AI and agentic systems that build on top of that foundation. But I still care most about what drew me in on day one: making complex systems legible, and turning data into decisions people can trust.
M.Sc. Information Technology
University of DhakaBangladesh Session: January 2017 - October 2018
B.Sc. Electrical & Electronic Engineering
Khulna University of Engineering & TechnologyBangladesh Session: April 2010 - November 2014
What Sets Me Apart
Most data scientists pick one lane. My edge is depth and range: a decade of hands-on machine learning and deep learning, now extended into AI, delivered at a scale and across domains that rarely overlap, from the factory floor of a global NYSE-listed manufacturer to satellite and climate data spanning an entire subcontinent.
Foundations, Then Frontier
The AI work isn't where I started; it's what I've grown into. A decade of hands-on machine learning and deep learning (forecasting, optimization, computer vision, graph neural networks) is the bedrock I build today's generative-AI and multi-agent systems on, not a layer of AI over a thin résumé.
On the Factory Floor
Inside one of the world's largest apparel manufacturers, the machines never stop. I put machine learning directly into the manufacturing process (spinning, knitting, dyeing, sewing, and more), catching quality issues and machine downtime early, often before they happen, so less material goes to waste and the floor runs measurably leaner.
Across the Entire Data Estate
Gildan's data doesn't sit in one neat place. It lives in on-prem datacenters, high-volume transactional systems, a Snowflake warehouse, and live POS feeds from Walmart, Amazon, and Target. I work across that whole estate, stitching fragmented, fast-moving data into a single picture the business can actually trust and act on.
A Subcontinent in View
Before manufacturing, my "dataset" was an entire region. I worked with Sentinel-2 satellite imagery and gridded climate simulations spanning South Asia, modeling crop health and climate risk at a scale most data scientists never get near, to support climate-resilient agriculture planning.
From Prototype to Production
A clever demo is easy; making AI dependable across an enterprise is the hard part. I build multi-agent platforms on the Microsoft Agent Framework and MCP, generative-AI portals with real access control, and the governance that lets all of it ship safely, not just impress in a demo but run in production.
Experience
Lead, Data Science
GILDAN One of the world's leading publicly traded apparel manufacturers (NYSE: GIL).
Development & Technical Execution
- Agentic Dev Platform: Building an internal Claude Code-style multi-agent developer assistant on the Microsoft Agent Framework, orchestrating specialized subordinate agents (code security review, data-validation & I/O-validation code generation, research, and an expanding skill pipeline) to standardize and accelerate the team's engineering workflow.
- Intelligent Production Planning: Developing an Enhanced Planning Tool for sewing to optimize line capacity. It predicts completion times and recommends lines to minimize changeover downtime, significantly boosting line efficiency.
- GenAI Decision Support: Led the creation of a Supply Chain AI Agent using Snowflake Cortex that allows leadership to query complex data in plain English, accelerating strategic decision-making.
- Operational Support AI: Built a RAG chatbot in Microsoft Copilot Studio to assist dyeing operators with standard procedures, ensuring instant access to the dyehouse knowledgebase for faster troubleshooting and compliance.
Leadership & Project Management
- Strategic Team Leadership: Orchestrating a high-performing cross-functional team (Data Scientists & BI Analysts) to architect and deploy Data Science & AI solutions that align with core business objectives and drive operational excellence.
- Data Science Governance: Established comprehensive governance frameworks and best practices for the department, standardizing coding protocols, documentation, and deliverables to ensure operational scalability and maintainability.
- Innovation Management: Championed the development of the "Invoice AI Agent", overseeing the project lifecycle from conception to delivery, which slashed manual finance workloads by approximately 60%.
- Mentorship & Operations: Mentoring Data Scientists & BI Analysts and streamlining team workflows, ensuring high-quality deliverables and fostering a culture of continuous technical growth.
Data Scientist
GILDAN One of the world's leading publicly traded apparel manufacturers (NYSE: GIL).
Development & Technical Execution
- Inventory Forecast & Optimization: Built advanced hierarchical forecasting models to predict spare parts tracking, directly preventing overstocking and ensuring plant operational continuity.
- Predictive Modeling (Fabric Dyeing): Developed Machine Learning models to predict fabric dyeing failures, allowing teams to intervene early and reduce costly material waste.
- Data Integration: Engineered ETL pipelines to ingest customer data from multiple sources (Delta Share, API) into Snowflake, creating a single source of truth for accurate cross-functional reporting.
- Generative Analytics: Developed a conversational agent (using PandasAI & Azure OpenAI) that leverages prompt chaining to generate SQL and Python code, enabling users to analyze complex tabular data via natural language.
- Real-time Analytics: Streamlined IoT data pipelines from spinning machines to provide live visibility of production performance in Snowflake, enabling immediate corrective actions.
Leadership & Project Management
- Project Ownership: Spearheaded the end-to-end delivery of an Azure OpenAI Analytics Chatbot, successfully democratizing advanced analytics for non-technical stakeholders across the organization.
- Stakeholder Management: Served as one of the major technical liaison between Data Science and Business units, translating complex requirements into actionable technical roadmaps to ensure project success and user adoption.
Data Analyst
International Maize and Wheat Improvement Center (CIMMYT) Non-profit international research organization for maize and wheat science.
Development & Technical Execution
- Recommendation System: Built an agricultural recommendation system using predictive ML models to deliver targeted, region-specific fertilizer recommendations to farmers and field officers.
- Anomaly Detection: Developed ML-driven anomaly detection models to surface irregularities and inefficiencies in regional fertilizer usage patterns.
- Media Intelligence: Designed automated NLP-based tools to scan online news, providing early warning signals for crop disease outbreaks across the region.
- Logistics Optimization: Developed a Logistics Optimization tool using Guided Local Search algorithm to optimize agricultural transport networks, achieving significant time and fuel cost savings.
- Satellite Data Analytics: Processed large-scale satellite imagery (Sentinel-2) and climate data to model crop health, supporting climate-resilient agriculture planning.
- Visualizations: Built interactive Streamlit dashboards to transform complex survey data into clear insights, empowering researchers to make data-driven decisions.
Leadership & Project Management
- Cross-Functional Synergy: Orchestrated collaboration between remote data scientists, field agronomists, and regional analysts, creating a cohesive ecosystem for integrating diverse climate and field datasets.
- Program Management: Supported and coordinated data strategy for the multi-country TAFSSA initiative, designing standardized protocols that unified agricultural data handling across South Asia.
Engineer
EDOTCO Bangladesh Co. Ltd Telecommunications Infrastructure Services Company in Asia.
Development & Technical Execution
- Process Automation: Automating repetitive data reporting tasks using software bots, freeing up team time for higher-value work.
- Performance Monitoring: Built tools to monitor power usage across telecom towers, helping to identify inefficiencies and reduce energy costs.
Leadership & Project Management
- Operational Leadership: Managed and upskilled a team of network engineers, establishing robust workflows for 24/7 network monitoring.
Projects & Research
Agentic Developer Assistant
Claude Code-style multi-agent assistant with subordinate skills: code security review, data & I/O validation code generation, research, and more.
Sewing Line Enhanced Planning Tool
Capacity optimization tool that predicts completion times and recommends optimal lines.
Inventory Forecast & Optimization
Hierarchical forecasting models to predict spare parts tracking, preventing overstocking.
Supply Chain AI Chatbot
Snowflake Cortex-powered chatbot for advanced analytics on supply chain datasets.
Predictive Modeling (Fabric Dyeing)
Machine Learning models to predict fabric dyeing failures, reducing costly material waste.
Generative Analytics Agent
Conversational agent generating SQL & Python code to analyze complex tabular data.
Dyeing Procedure Assistant
RAG chatbot providing instant troubleshooting support and procedure access for dyeing operators.
Crop Disease Epidemiology Tool
Web data-mining and NLP tool for tracking crop diseases.
Agri-Transport Optimization
Logistic tool for optimization of transport networks in the agriculture domain.
Field Boundary Detection [Personal Project]
Detect Field Boundaries using Holistically-Nested Edge Detection (HED) on airborne images.
Chemical Property Prediction [Personal Project]
Physicochemical properties prediction with Hybrid-GICN.
Technical Skills
Languages & Big Data
ML & Modeling
Generative AI & Agents
Data Engineering & Processing
Databases, Warehouse & Cloud
Geospatial & Visualization
MLOps & DevOps
Mentorship & Supervision
Scientific Programming with Python
Tailor-Made Training (TMT+) Programme BARI, Bangladesh | 2021Geospatial Data Analysis & ML
Spatiotemporal Machine Learning with Python BARI, Bangladesh | 2021Project Supervision
Geo-Information Science and Earth Observation ITC, University of Twente, Netherlands | 2022Certifications & Training
Spatial Regression in R
GEMS Learning CIMMYT & Univ. of Minnesota | 2023Geostatistics and Interpolation in R
GEMS Learning CIMMYT & Univ. of Minnesota | 2023Open Source Scientific Computing
AgroGeospatial Big Data Analysis ITC, University of Twente | 2022Deep Learning Specialization
DeepLearning.AI 2020Algorithms for DNA Sequencing
John Hopkins University 2020Food Security and Sustainability
Crop Production Wageningen University & Research | 2020Data Visualization with Seaborn
DataCamp 2019Data Science & Big Data Foundations
IBM 2017Selected Publications
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Advancing crop disease early warning in South Asia by complementing expert surveys with internet media scraping [Link]
Climate Resilience and Sustainability, 3, e78. (2024)
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The optimization of conservation agriculture practices requires attention to location-specific performance: evidence from large scale gridded simulations across south asia [Link]
Field Crops Research, Elsevier (2022)
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Climates' dual grip: Mapping upper and lower bounds for thermal stress risk for rice, wheat, and maize in Bangladesh [Link]
Technical Report (2023)
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Personality detection from text using convolutional neural network [Link]
ICASERT, IEEE (2019)
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Innovative new crowd sourcing tool for gathering crop disease reports developed in South Asia [Link]
ARRCC Programme Newsletter (2020)
Get In Touch
Feel free to reach out for collaborations or opportunities.