Machine Learning Engineer and Data Scientist with 3+ years of experience in predictive modeling, NLP, and scalable AI/ML pipelines. Proficient in Python, TensorFlow, and PyTorch, with expertise in cloud deployment and data visualization. Skilled at transforming data into actionable insights and effectively communicating complex analyses. Passionate about driving data-driven decision-making and business impact.
- Email: riasatfaizan468@gmail.com
- LinkedIn: Faizan Riasat
- Developed a complete sales forecasting system using time-series analysis, integrating models such as ARIMA, Prophet, and LSTM to predict sales trends and seasonality.
- Deployed a real-time dashboard for forecast visualization, enabling inventory optimization and strategic planning.
- Tools Used: Python, AWS, Flask, ARIMA, Prophet, LSTM
- Built an NLP-based system for analyzing customer feedback across channels (social media, emails, and surveys), leveraging BERT for sentiment analysis and topic modeling.
- Deployed a cloud-based REST API for real-time feedback classification and provided a dashboard for sentiment trends and actionable insights.
- Tools Used: Python, BERT, Django, REST API, AWS
- Developed a computer vision system for real-time inventory monitoring using IoT-enabled cameras and YOLOv5, with automated alerts for low stock.
- Implemented a cloud-based dashboard for tracking inventory, predicting shortages, and optimizing reorder times with SKU-level insights.
- Tools Used: Python, YOLOv5, OpenCV, Flask, AWS IoT, Streamlit
- Created a machine learning pipeline to detect fraudulent transactions using supervised learning and anomaly detection algorithms.
- Deployed the solution via Docker and Kubernetes for scalable, real-time fraud detection, with a custom-built analytics dashboard to track fraud patterns.
- Tools Used: Python, XGBoost, Random Forest, Isolation Forest, Docker, Kubernetes, AWS