Developing software within a microservices architecture using Python and PySpark
deploying solutions as REST APIs with FastAPI
Constructing scalable data pipelines utilizing scheduler and executor frameworks for data ingestion and transformation
Implementing machine learning models using supervised techniques including Classification and Regression, unsupervised methods including Clustering and Association, and reinforcement learning approaches including Contextual Armed Bandits for financial applications such as risk assessment, fraud detection, and credit scoring
Designing and deploying deep learning models including ANN, CNN, and RNN using TensorFlow, Keras, and PyTorch for predictive analytics and financial forecasting
Applying statistical methods for data analysis, hypothesis testing, and model validation to extract insights from financial data
+3 more