* Ability to aggregate, normalize and process data by authoring predictive algorithms to synthesize and present actionable data insights.
* Experience in at least one of the following fields: machine learning, data visualization, statistical modeling, data mining, or information retrieval
* Proficiency in analysis (e.g. R, SAS, Matlab) packages, programming languages (e.g. Java, Python, Ruby) as well as the ability to implement, maintain, and troubleshoot big data infrastructure, such as distributed processing paradigms, stream processing and databases such as Hadoop, Storm, SQL and Solr
* Ability to solve complex problems in a fast-paced environment with limited guidance.
* An eye for quality and a willingness to do what is necessary to achieve deadlines in a dynamic environment with frequent priority changes is required.
* Able to work efficiently in teams and/or as an individual
* Good oral and written communication skills.
* Bachelor’s degree in Applied Statistics, Economics, Engineering, Mathematics, Finance, Computer Science, or Operations Research with 2-5 years applicable experience; or Master’s degree with 1-3 years applicable experience (preferred)
* 1 to 3 years’ experience in advanced analytics, model building, statistical modeling, optimization, and machine learning algorithms including supervised and unsupervised learning, boosting and ensemble methods
**Environmental Working Conditions & Physical Effort:**
* Typically works in an office environment with adequate lighting and ventilation and a normal range of temperature and noise level.
* Work assignments are diversified. Examples of past precedent are used to resolve work problems. New alternatives may be developed to resolve problems.
* A frequent volume of work and deadlines impose strain on routine basis.
* Minimal physical effort is required. Work is mostly sedentary but does require walking, standing, bending, reaching, lifting or carrying objects that typically weigh less than 10 lbs.