Ritaja Sengupta

Current focus: Data Engineering and Analytics/Data Science topics. - Leading teams on various Search and Discovery topics on Data Lake. - Co-architecting cloud migration strategies for Data Lake and components.

Machine Learning: - Developing Deep Learning Models (Recurrent, Convolutional, Feed-forward architectures) for classification tasks. (Tensorflow) - Architecting containerised training pipeline on GPU clusters (Docker, Nvidia-Docker,) DevOps: - Architecting cloud agnostic infrastructure (Ansible, Kubernetes) Data Engineering: - Big Data Pipeline Engineering , ETL, Distributed Algorithms design for big data sets (Spark, Cassandra, Elasticsearch, Redis) Clouds: Google, Microsoft; IBM.

- Developing recommendation engines for intelligent user-product predictions - Working on Collaborative filtering, Defining persistence models with Pandas, PostgreSQL, Python - Working on Sparse data models, defining efficient persistence - Implementing Matrix Factorzsation, SVD, LSI - R&D on machine learning algorithms for recommendation systems - Latent Semantic Analysis using NLP, building recommendation systems and evaluation matrices based on browser activity and product catalogues

- Research on Risk Scoring of e-commerce transactions using machine learning Technology/Framework/Tools: Python, Pandas, Theano, Keras(also contributer), Lasagne, R, MongoDB, Gradle - Development and Automation of framework to test Payment processes and REST-ful services. Technology/Framework/Tools: Java, Spring Framework, Maven, MongoDB, Neo4j, TestNG, Selenium, REST-Assured

- Software Architecture Design - Web driver for automation testing using Selenium for Java - Apache POI library integration - Zephyr for JIRA - SOAP UI for RESTful webservices

Providing IT solutions to a German Energy major and automating sub-processes in the domain.

Paint Tool using Python programming with basic image editing capabilities.

Studying, documenting the process followed at the department to develop deliverable for the client and also to suggest improvements to increase the overall efficiency of the process.

Machine Learning, Distributed Systems, Advanced Computer Networks, Techniques in Artificial Intelligence