Required Skills:

• 2+ year’s professional experience working within the business intelligence or data science field with experience in development of advanced analytics.

• Experience and skills in data mining, data analysis, data tools, design, build and implementation of models, algorithms as well as creating, running and interpretation of simulations.

• Experience using web services for data science such as Azure, AWS, Google or Redshift.

• Solid experience with R and other data science toolkits and supporting MPP data engines such as GreenPlum.

• Knowledge and experience using statistical computer languages to manipulate data, develop insights from large data sets and make recommendations on actions. Languages such as R, Python and SQL are essential.

• Proficiency with advanced statistical techniques such as various regression modeling (linear, logistic, polynomial, etc.), various forecasting methods, distribution properties and experience with applications.

• General knowledge of various data mining techniques such as tracking patterns, classification, association, outlier, clustering, regression and prediction for examples.

• Solid knowledge and experience with data visualization tools such as Power BI, Tableau, GGPlot and presenting for stakeholders.

• Proficiency with distributed/computing data tools such as Map/Reduce, Hadoop, Hive and Spark.

• Proficiency with various types of NoSQL databases (document, column, graph, key-value stores, etc.).

• Knowledge of analyzing data from 3rd party providers and further combining with other data sources to draw inferences, correlations, clusters and or scenario analysis.

• General knowledge of PCI standards and regulations.

• General knowledge and experience working within an agile environment.

• General knowledge of MS office tools Word, Excel, PowerPoint, Visio and Outlook.

• Strong problem solving skills with an emphasis on consumer back-office tools and product development.

• Good verbal, written and graphic communication skills. Ability to tell a story with data and data visualizations.

• Solid understanding of machine learning techniques and algorithms.

• Detailed-oriented in data validation, A/B testing, and monitoring of model or algorithm resul

• Ability to be skeptical of findings, correlations, assumptions and overall conclusions to ensure proper analysis and evaluation is done prior to submission to stakeholders.

• Innovative with the ability to leverage data to produce offerings that solve for inefficiencies and distinguish product offerings.

• Ability and willingness to consult with business stakeholders, interpret findings and make recommendations to aid decision making.

• Ability to troubleshoot data integrity issues involving multiple data sources including 3rd party data, and further analyze data for validity and completeness.

• Excellent communication skills and ability to translate the complex to simple and easier terms for business leaders and users of data.

• Ability to communicate to a wide audience including business and technical teams, high-level executives and clients.