Summary of Responsibilities:
Performs data-driven analyses, problem solving and algorithm development through the systematic application of mathematics, statistics and computer science with cutting edge data mining and machine learning technologies. Tackles relevant business concerns by providing strategic intelligence for fundamental and high impact business questions that directly impact the direction of the Company. Works closely with business partners and stakeholders to transform findings into actionable business opportunities.
Works on projects to apply data science to business problems and opportunites.
Meets with business units to understand current problems and opportunities to be addressed. Communicates regularly with customers through model creation and implementation.
Assembles data sets and variables from disparate sources and analyzes using appropriate quantitative methodologies, computational frameworks and systems.
Collects large sets of structured data, cleans and validates to ensure accuracy, completeness and uniformity.
Identifies data limitations and flaws, communicates their impacts, and takes appropriate steps to improve the data.
Uses appropriate methodologies to develop algorithms and predictive models. Validates models and measures performance.
Devises and applies models and algorithms to mine data, identify patterns and trends, and discover solutions and opportunities.
Pilots/tests and develops statistical and predictive models.
Designs and analyzes experiments.
Critically and logically evaluates the costs, risks and benefits of alternatives before coming to a solution.
Probes and looks past symptoms to determine the underlying causes of problems and issues.
Disseminates findings to non-technical audiences through a variety of media, including interactive visualizations, reports and presentations.
Performs other duties as assigned by management.
Two-plus years with B.S. or one-plus year with M.S. or Ph.D. experience working as a data scientist.
Proven educational or work experience using statisical techniques for supervised and unsupervised learning and model development, including regression, classification, time series, clustering, survival analysis, random forests and ensemble methods, analysis of variance and experimental design, etc.
Proven educational or work experience developing probabilistic models and machine learning algorithms and implementing models in a production environment.
Proven educational or work experience using statistical analysis software, such as R or Python programming languages.
Demonstrated experienced user of analytics software such as SQL, Tableau, KNIME, Azure, AWS or Alteryx.
Demonstrated advanced user of Microsoft Office suite, especially Excel.
Demonstrated exceptional problem-solving skills and willingness to learn new concepts, methods and technologies.
Proven ability to work in a highly collaborative environment.
Demonstrated outstanding communication skills. Ability to translate complex concepts in a non‑technical manner.
Works in an office setting and remains in a continuous stationary position for long periods of time while working at a desk, on a computer, or while in meetings or making presentations.
Requires visual acuity to read a variety of correspondence, reports and forms, and to prepare and analyze data.
B.S. or M.S. or Ph.D. in quantitative field such as statistics, applied mathematics, economics, computer science, engineering, or other field that is highly analytical/quantitative. Ph.D. preferred.
Computer Skills and Knowledge of Hardware & Software Required:
Certifications & Licenses (i.e., Series 6 & 63, CPA, etc.):
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