Data Scientist
Roles and Responsibilities include but not limited to:
• Data exploration - Explore large data sets using a variety of tools to build model ready data products and provide any requirements to ETL developers to productize.
• Model Building - Description: Leverage analytics tools like SAS to build complex statistical and machine learning models to build predictive and prescriptive strategies.
• Adhoc Insight Generation - Description: Quickly explore data and apply descriptive statistics to provide rapid insights for the business customer.
• Create data mining architectures/models/protocols, statistical reporting, and data analysis methodologies to identify trends in large data sets. Analysis may have many applications such as to address a business issue or provide a competitive advantage for the organization
• Utilizes strong statistical and data visualization skills
• Uses and applies technical principles, theories, and concepts
• Demonstrates the skill and ability to perform professional tasks
• Develops recommended solutions to technical problems as assigned
• Submits work for review of soundness of technical judgment, quality, and accuracy
• Contributes to the completion of assigned technical tasks
Basic Qualifications
• Must have one of the following:
o Bachelor’s degree in Computer Science, Social Sciences, Physical Sciences, Statistics, or related discipline with a minimum of 5 years of statistics experience
o Master’s degree in Computer Science, Social Sciences, Physical Sciences, Statistics, or related discipline with a minimum of 3 years of statistics experience
• Experience with customer churn and lead generation modeling.
• Knowledge of statistics, including sample design and probability sampling techniques, survey and experimental design, and measures of precision.
• Knowledge of industry developments, business practices, and technical developments to meet business needs.
• Ability to use computer-based data and operating systems, programming languages, and statistical packages (R, SAS, etc.)
• Experience working with large datasets in a Hadoop environment.
• Experience with SQL in Oracle and Teradata environments.
• Ability to provide technical guidance related to data design, data collection, and statistical analysis.
• Ability to communicate facts or ideas orally and in writing, when answering questions, giving directions, providing information, preparing reports/presentations, and in preparing documentation.
• Ability to provide relevant leadership and support to management, peers, and customers for data science best practices and procedures.
Preferred Qualifications:
• Master's degree or PhD in related field
• Significant experience with R, Python, C++, Hadoop, SQL Database/Coding, Apache Spark, Machine Learning, Natural Language Processing, and visualization tools such as Tableau
• Demonstrated experience working with unstructured data