Job Description: • In this role, the Data Scientist collects and analyzes statistics and information from multiple sources to spot trends and to gain maximum insight that can give the company a competitive advantage and communicates informed conclusions and recommendations across an organization's leadership structure. Strategizes and identifies unique opportunities to locate and collect new data, explores and mines data from many angles, and determines what it means. Communicates data findings to both business and IT leaders to influence how an organization approaches and meets business challenges of an evolving customer base and changing marketplace, using strong business acumen. Finds and recommends new uses for existing data sources; designs, modifies, and builds new data processes; and builds large, complex data sets. Tools and Technologies: • Programming languages: SQL, Python, PySpark, Shell Scripting, PowerShell • Data visualization: Tableau Desktop & Server, Power BI, Looker, Jupyter Notebooks • Other frameworks: git, GitHub, SSH Secure Shell, Putty, XML, JSON, SQL Workbench • Big data platforms: Apache Spark, Spark SQL, Hive, HDFS, MapReduce, Azure Data Lake • Cloud platforms: Amazon Web Services (AWS), EC2, S3, RDS, VPC, EMR, SNS, IAM, Redshift, CloudWatch, SQS, Route53, CloudFront, Athena, Kinesis, QuickSight, Lambda. • Statistical tools: Snowflake, Redshift, Oracle, MySQL, Microsoft SQL Server, PostgreSQL