Bachelor's or advanced degree in computer science, applied math, statistics or other relevant quantitative discipline, or equivalent industry experience
14 or more years of relevant work experience with 6 or more years as a data scientist, analyst, or statistical modeler.
2 years of experience in developing and deploying products using Docker, Kubernetes, and the containerization technology stack
3 years of experience in development of advanced machine learning and deep learning models such as RNN, LSTM, and specifically Graph Neural Networks(GNN)
3 years of experience in modern data mining and data science techniques (e.g., regressions, decision trees, ensemble algorithms, neural networks, time series analytics, clustering, anomaly detection, text analytics, etc.)
Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, etc.
Experience with Big Data and analytics in general leveraging technologies like Hadoop, Spark, and MapReduce
Experience in using NLP, BI, Graph Databases like Neo4j/OrientDB/Neptune
Programming in Python and R using distributed frameworks like PySpark, Spark, SparkR
Candidate with background in telecom preferred, is a plus