
Seasoned Data Scientist with background in designing and implementing data-driven solutions for various business challenges. Experience includes predictive modeling, artificial intelligence, machine learning, and big data technologies. Strengths lie in strong analytical thinking, problem-solving skills, and ability to translate complex data into actionable insights. Previous work has resulted in significant improvements in decision-making processes and business performance.
Programming & Scripting: Python, SQL, PL/SQL, C#, R
Machine Learning & AI: Supervised & unsupervised learning, deep learning (CNNs, Transformers), ensemble methods, reinforcement learning (DQN), feature engineering, time series forecasting
Data Engineering & Big Data: SQL Server, MongoDB, PostgreSQL, ETL pipelines, data extraction & transformation
Frameworks & Tools: TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy, Seaborn, Matplotlib, Jupiter Notebook, Git/GitHub, API development
Cloud & Platforms: AWS (S3, EC2, SageMaker, Glue), Azure (ML Services, Blob Storage), Google Colab, Anaconda
Visualization & BI: Tableau, Power BI, Excel (PivotTables, VLOOKUP, charts)
Operating Systems: Windows, Linux/Unix