Job Description :
Location – Bloomington, IL

Requested Skills:

Digital Analytics (Senior level digital experience specialist (languages SAS, SPARK, SQL, Java)

· Breadth of knowledge and expertise in programming (R, Python), Descriptive Inferential, and database functionality (SQL, Hadoop, SAS)

· Applies an expert understanding of data tools, practices, applications, programming languages and environments to assignments

· Enable solution modernization activities through design and development related work items and architectural engagement

· Develop expertise with multiple machine learning algorithms and data science techniques, such as exploratory data analysis, generative and discriminative predictive modeling , grapy theory, recommender systems, text analytics, computer vision, deep learning, optimization and validation

· Prepare and manipulates data for use in development of statistical and predictive models

· Assists in development of project parameters, statistical models or analysis as needed

· Provides high level support for problem and issue resolution and provides technical consultation and direction to business and product team members

· Utilizes strong business and technical knowledge at least once than data discipline across multiple platform/operating system to develop and support data, databases or product.

· Is sought out as a project matter expert and provides comprehensive data knowledge on various design and access techniques for complex efforts

· Influences and provides the direction the data practices and data infrastructure needed to support data services and automation

· Influences and identifies data standards , best practices coding and testing standards to promote consistency and re-use.

· Conducts research and integrate industry best practices into data trends, enterprise technology processes and potential solutions

· Drives required product testing practices and solutions to ensure product quality

· Defines and tests data requirements for the movement , replication, synchronization and validation of data. Applies understanding of product deign , data design and movement and test to ensure quality outcomes

· Identifies critical and emerging technologies that will support and extend our quantitative analytics capabilities