Data Scientist

Demonstrates some abilities and/or a proven record of success with identifying and addressing client needs using the following techniques, tools and programs:Machine Learning;Deep Learning;Natural Language Processing (NLP);Generative AI;Programming skills (e.g., Python, R, Java, SQL, Jupyter Notebooks, IDEs);Data wrangling/modeling;Structured data storage technologies (e.g., SQL Server, PostgreSQL);Unstructured data storage technologies (e.g., MongoDB, Neo4j);Big data tools (e.g., Hadoop, Spark/PySpark, Kafka);Testing tool experiences (e.g., Selenium, Cucumber, Postman);Visualization tools (e.g., Tableau, Zoomdata, PowerBI);DevOps technologies & tools (e.g., Git, Jenkins, Docke