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Data Scientist
2 months ago
As the Data Scientist / ML engineer, you are expected to engineer, develop, and deliver ML models using real time network data to enable decision making and drive insights.
Key responsibilities will be -
- Experience in designing, developing, optimizing, and troubleshooting ML model applications in Kubernetes environment with Spark, Java, and Python environment with databases like Apache Druid, Oracle, Cassandra, and/or Kafka as the backend
- Collaborate with team to drive the technical roadmap and guide development and implementation of new data driven business solution
- Collaborate with data engineers and solution architects to overcome roadblocks, challenges in building the models.
Skills:
- Bachelor's or advanced degree in computer science, applied math, statistics or other relevant quantitative discipline, or equivalent industry experience
- 12 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/Orient DB/Neptune
- Programming in Python and R using distributed frameworks like Py-Spark, Spark, SparkR
- Candidate with background in telecom is needed.
