Data Scientist

Job Description:

- Responsible for capturing customer interaction data and blending, mining, processing and distilling the vast amounts of data into meaningful, valuable insights.
- Build large systematic reports and one-off small pieces of exploratory analysis, from multiple disparate datasets.
- Work across the business to identify analytical requirements and areas for further research.
- Communicate findings, results and progress with appropriate visualizations, reports, blogs, or other medium.
- Define a consistent process for publishing findings and results internally and externally.
- Advance the organization's understanding of customer behavior across its digital portfolio.
- Perform statistical modeling, querying, and data mining on large datasets.
- Perform machine-learning, data mining/predictive analytics, A B and multi-variate testing, and Natural language processing/text mining.
- Design relational databases and conduct efficient information retrieval (SQL).

Requirements:
- Master's degree (or higher) (or foreign education equivalent) in Engineering, Statistics, Data Science or a related field plus three (3) years of experience performing advanced analytics using predictive modeling and machine learning algorithms, or alternatively, Bachelor's degree (or foreign education equivalent) in Engineering, Statistics, Data Science or a related field plus five (5) years of experience performing advanced analytics using predictive modeling and machine learning algorithms.

Candidate must also possess:
- Demonstrated Expertise ("DE") with relational databases to extract, transform and query data from multiple heterogenous datasources.
- DE in statistical analyses using R, Python, or SAS using the scientific method.
- DE in application of machine learning programs in R/Python to generate insight from complex data, make predictions and assist in task automation.
- DE building and designing visual analytic reporting dashboards and custom-built visualizations for communicating insight from complex data to project stakeholders to assist decision making.
- DE using Git for version control and package dependency management for programming languages R, Python, Java and JavaScript for code development.