Description
Responsibilities:- Leverage large sets of structured and unstructured data to develop tactical and strategic insights.
- Collaborate with analytic and data teams to set objectives, approaches, and work plans.
- Research and evaluate new analytical methodologies, approaches, and solutions.
- Develop and validate statistical forecasting models and tools.
- Interpret and communicate analytic results to analytical and non-analytical business partners and executive decision makers.
Qualifications:
- Advanced degree in a quantitative field such as applied statistics, mathematics, management science, engineering, economics, computer science, or operations research (Master's degree required, PhD preferred)
- 4+ years experience in advanced analytics and model development and validation. This includes standard regression techniques for forecasting, as well as machine learning approaches for classification and regression.
- Experience with a Scripting language such as Python (strongly preferred) or Lua.
- Previous work with Python's numerical computing stack and machine learning libraries is a big plus.
- Experience with a statistical package such as R, SAS, or Matlab.
- Experience writing SQL queries and linking SQL and Python or R to enable read/write to the database.