Data Scientist  

• Analyzes raw information through statistical analysis to discover trends or patterns that can be used for building data products to extract valuable business insights.
• Collaborates with the company’s business clients to identify gaps and structure problems as well as to propose solutions and strategies to business challenges.
• Leads trainings and informational sessions on statistics.

Junior Level:

• Must have at least 2 year of experience manipulating data sets and building statistical models
• Uses predictive modeling to increase and optimize customer experiences, revenue generation and other business outcomes.
• Utilizes machine learning algorithms and models and presents them using data visualization techniques.
• Has familiarity with statistical software packages such as R, Python, SAS and Scala as well as different end-to-end data science and advanced analytics tools such as Microsoft Azure Machine Learning.

Mid-Level:

• Must have at least 2-4 years of experience manipulating data sets and building statistical models
• Familiar with the following software/tools:
• Coding knowledge and experience with several languages: C, C++, Java, JavaScript, etc.
• Knowledge and experience in statistical and data mining techniques
• Experience querying databases and using statistical computer languages
• Experience using web services: Redshift, S3, Spark, etc.
• Has strong familiarity knowledge with statistical software packages such as R, Python, SAS and Scala as well as different end-to-end data science and advanced analytics tools such as Microsoft Azure Machine Learning.
• Exceptional understanding of the different software utilities for data and computation such as Hadoop, Apache Spark and Impala.

Senior Level:

• Must have at least 5-7 years of experience manipulating data sets and building statistical models
• Familiar with the following software/tools:
• Coding knowledge and experience with several languages: C, C++, Java, JavaScript, etc.
• Knowledge and experience in statistical and data mining techniques
• Experience querying databases and using statistical computer languages
• Experience using web services: Redshift, S3, Spark, etc.
• Has strong knowledge with statistical software packages such as R, Python, SAS and Scala as well as different end-to-end data science and advanced analytics tools such as Microsoft Azure Machine Learning.
• Exceptional understanding of the different software utilities for data and computation such as Hadoop, Apache Spark and Impala.