Abdul Syed

About Abdul Syed

Data Scientist with 5+ of experience in applying advanced data analytics, machine learning, and statistical techniques to solve complex business problems. Skilled in developing and deploying machine learning models, including Linear/Logistic Regression, Random Forests, and XGBoost, achieving significant improvements in predictive accuracy. Capabilities include building scalable data pipelines, implementing real-time analytics systems, and deploying models for use cases including predictive analytics, customer segmentation, fraud detection, recommendation systems, and natural language processing (NLP). Experienced with data visualization tools including Tableau, Power BI, and custom dashboard solutions for presenting analytical results to technical and non-technical stakeholders. Skilled in end-to-end project execution, from requirement gathering to model deployment, within Agile development environments. Strong focus on production-grade model implementation, performance optimization, and continuous integration of AI/ML advancements into enterprise workflows.

Experience

1. Data Scientist

   Capital One

   Jul 2023 — Present · US

   Applied Agile methodologies to adapt to evolving project requirements and deliver iterative, high-quality solutions on time.Conducted statistical hypothesis testing to validate key variable relationships and inform strategic decisions.Built and deployed NLP models for sentiment analysis to extract insights from customer feedback.Designed interactive Tableau dashboards to visualize complex data and support strategic decision-making.Developed and deployed supervised learning models such as Linear/Logistic Regression, Decision Trees, Random Forests, and SVM for classification and regression tasks, improving prediction accuracy by 15%.Created AI models for demand forecasting, reducing forecast error by 18% and enhancing inventory accuracy.Leveraged ensemble learning methods like XGBoost and Gradient Boosting to enhance model accuracy and reduce overfitting, resulting in a 25% performance improvement.Designed and trained deep learning models, including CNNs for image classification and RNNs/LSTMs for time series forecasting, achieving 30% improved model accuracy.Leveraged AWS EC2 for scalable computing, optimizing data processing tasks and reducing model training time by 50%.Developed custom visualizations using Matplotlib, & Seaborn in Python to communicate complex data trends, improving client understanding of data-driven recommendations by 15%.Optimized MySQL database schema to enhance data storage, retrieval efficiency, and scalability, ensuring robust performance.

Education

• Lamar University

  Master of Science - MS, Management Information Systems

• Jawaharlal Nehru Technological University

  Bachelor of Technology, Computer Science and Engineering