Job Summary
Designs, develops and programs methods, processes, and systems to consolidate and analyze unstructured, diverse “big data” sources to generate actionable insights and solutions for client services and product enhancement. Interacts with product and service teams to identify questions and issues for data analysis and experiments. Develops and codes software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources. Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers.

Job Description
Analyze data and build descriptive and predictive models in the areas of capacity planning, anomaly detection, workload optimization, customer segmentation and business performance.
Mine information for previously unknown patterns and insights hidden in these assets and leverage them for competitive advantage.
The problems solved will be at the cutting edge of technology and will lie at the intersection of science, engineering and business acumen.
Be part of a highly skilled agile team and within a strongly focused DevOps culture.

Job Requirements
Able to apply techniques such as classification, clustering, regression, association, anomaly detection, time series forecasting, Hidden Markov models and Bayesian inference to solve pragmatic business problems
Able to design working models and implement them on Big Data systems using Map Reduce or Spark frameworks.
Familiar with Hadoop, Pig, Hive, Scope, Cosmos, or similar technologies.
Able to work within an agile, iterative DevOps development process

12 + year; 8 + year with a Masters
Experience with statistical programming environments like R, Matlab or Octave
Fluent in one or more object oriented languages like C#, C++, Scala, Java, and scripting languages like Python or Ruby
Experience with statistical programming environments like R, Matlab or Octave
Degree in Math, Computer Science, Data Mining, Machine Learning, Statistics or other quantitative discipline
Plus: Experience with Cloudera or Pivotal Hadoop distributions, Experience with Pivotal HD, GemFireXD, HAWQ

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