
Shariful Islam Foysal
Verified Expert in Engineering
Data Science Developer
London, United Kingdom
Toptal member since December 17, 2019
Foysal is a data science and applied machine learning professional with extensive experience in data analytics, statistical analysis, machine learning, and data engineering. He has experience working in a successful startup and a tech giant with a massive volume of data.
Portfolio
Experience
- Data Science - 8 years
- Machine Learning - 7 years
- Python - 7 years
- React - 5 years
- Data Extraction - 5 years
- SQL - 4 years
- Chatbots - 3 years
- Large Language Models (LLMs) - 2 years
Availability
Preferred Environment
Visual Studio Code (VS Code), GitHub, Linux, MacOS
The most amazing...
...thing I've built is a complete model for real-time dynamic pricing for one of the largest ride-hailing platforms in South Asia.
Work Experience
Business Intelligence Engineer
Amazon
- Engineered a Text to SQL generation service using LangChain and Claude LLM featuring a Slack bot interface for users and a web app for RAG knowledge management. The solution serves 500+ users, reducing query development time by 2,500 hours monthly.
- Led the development of an enterprise web app using React and AWS services that automated catalog management for 400,000+ products. Implemented access control, real-time validation, and analytics dashboard, saving 10,000+ hours annually.
- Built an LGBM-based ML model for new product demand forecasting. The solution predicts 6-month aggregated demand for products with 6-12-month lead times, enabling data-driven inventory decisions and improving forecast accuracy over heuristic methods.
- Engineered automation system that evaluates deal eligibility across global marketplaces processes inventory, profitability, and dynamic pricing logic, generating optimized deals that reduced manual effort by 500+ hours and improved decision accuracy.
- Built Quicksight dashboards monitoring data quality metrics across global marketplaces. The solution tracks completeness, vendor terms, and buying attributes for 400,000+ products, enabling data-driven decisions and improving operational efficiency.
Data Scientist, Machine Learning
Pathao
- Built machine learning (ML) models for demand prediction. Improved data extraction processes.
- Built end-to-end ETL pipelines for real-time analytics.
- Designed statistical experiments, A/B tests, and multi-armed bandit tests.
- Built automated FinOps Tableau, Google Sheets, and Excel dashboards for regular business health monitoring.
- Developed an ML model-based tool for user segmentation and experimentation for incentive burn optimization.
- Automated processes for drivers' payments, which saved 1,250 man-hours.
- Built a financial forecasting platform combining Python ML back end with Excel interface. The system processes historical data to generate predictions, enabling business leaders to track and adjust forecasts for strategic planning.
Research Engineer
Pi Labs Bangladesh LTD
- Developed a license plate recognition system using an image processing technique in the automated parking system.
- Built a web scraping bot to collect information on the target user base from different sources for use in digital marketing.
- Developed a Tesseract-based custom OCR solution to extract specific information from image documents.
Research Associate
Dingi Technologies LTD
- Improved GPS signal accuracy by 8% from vehicle tracking devices by implementing the Kalman Filter.
- Designed a fuel measurement system for a vehicle tracking device.
Experience
LLM-based Slack Bot for Natural Language to SQL Query Generation
The system features a user-friendly Slack bot interface for query requests and a React web application for knowledge base management. Implemented robust security controls through authentication and built automated guardrails for query validation and blocking harmful content. The solution is highly scalable and deployed in the cloud.
Achieved significant business impact by reducing query development time by 2,500 hours monthly and democratizing data access across the organization. The system serves 500+ users and maintains high accuracy through continuous feedback mechanisms and automated performance monitoring.
Real-time Dynamic Pricing Engine for a Ride-hailing Platform
Built a robust machine learning pipeline using time-series forecasting models to predict hyperlocal demand and supply patterns. Implemented an adaptive pricing algorithm considering multiple factors, including historical patterns, current market conditions, weather impact, and special events. The system processes real-time data streams to adjust prices dynamically, ensuring optimal market balance across different city zones.
The architecture leverages containerized microservices for scalability, with automated model retraining pipelines and A/B testing capabilities. Implemented comprehensive monitoring and alerting systems to track key performance metrics,s including driver utilization, rider wait times, and market equilibrium indicators.
New Product Demand Forecasting System
Built an end-to-end ML pipeline that processes historical sales data, product attributes, and market indicators to generate accurate demand predictions. The system incorporates multiple granularity levels of product attributes and seasonality patterns to handle the cold-start problem inherent in new product forecasting. Implemented a specialized version (2.0) for newly launched products, with modified feature engineering and hyperparameter optimization.
The solution significantly improved forecast accuracy over traditional heuristic methods, enabling better inventory planning and reducing stockouts while optimizing working capital. The system processes forecasts across multiple European marketplaces, supporting strategic product design and supply chain planning decisions.
Education
Bachelor's Degree in Electrical and Electronic Engineering
Bangladesh University of Engineering and Technology (BUET) - Dhaka, Bangladesh
Certifications
Deep Learning Specialization
deeplearning.ai
Skills
Libraries/APIs
Scikit-learn, TensorFlow, PyTorch, OpenCV, React, Node.js
Tools
Tableau, Microsoft Power BI, Power Pivot, ChatGPT, Microsoft Excel, Apache Airflow, GitHub, Amazon QuickSight
Languages
SQL, Python, C, C#, JavaScript
Paradigms
Business Intelligence (BI), Microservices Architecture
Platforms
Linux, MacOS, Amazon Web Services (AWS), Visual Studio Code (VS Code)
Storage
MySQL, PostgreSQL, Redshift, Google Cloud
Frameworks
Flask, Scrapy, Selenium, LightGBM
Other
Data Analytics, Clustering, Regression, Data Science, Data Engineering, Google Colaboratory (Colab), Data Analysis, Algorithms, DAX, Dashboards, API Integration, Data Mining, Data Scraping, Data Modeling, Chatbots, Machine Learning, eCommerce, Grocery Delivery, Food, Google BigQuery, Data Visualization, Statistical Analysis, Web Scraping, Version Control Systems, Models, Data Extraction, Data Structures, Artificial Intelligence (AI), Statistics, LangChain, Large Language Models (LLMs), Retrieval-augmented Generation (RAG), Time Series Forecasting, A/B Testing, Demand Forecasting, RESTful Services, APIs, Web Development
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