Lead Data Scientist - WAH or any Humana Office

The Lead Data Scientist uses mathematics, statistics, modeling, business analysis, and technology to transform high volumes of complex data into advanced analytic solutions. The Lead Data Scientist works on problems of diverse scope and complexity ranging from moderate to substantial.
The Lead Data Scientist develops, maintains, and collects structured and unstructured data sets for analysis and reporting. Creates reports, projections, models, and presentations to support business strategy and tactics. Advises executives to develop functional strategies (often segment specific) on matters of significance. Exercises independent judgment and decision making on complex issues regarding job duties and related tasks, and works under minimal supervision, Uses independent judgment requiring analysis of variable factors and determining the best course of action.
Required Qualifications:
Master's Degree in a quantitative, informatics, mathematics or analytics domain
Demonstrated success in a commercial environment with building predictive models, including usage of best practices for evaluating models
In addition to traditional learning methods such as generalized linear models, has some experience building models using boosting, random forests, deep learning, or other modern machine learning methods
Extensive experience using either R or Python to build and analyze predictive models
Experience analyzing datasets with many attributes and many observations
Experience implementing models in a production context for systems or users to respond to
Experience understanding the business purposes, context, and constraints for a modeling projects, and delivering a successful result
Experience communicating results to stakeholders, management, and others
Has demonstrated an ability to come up with innovative ideas and bring them to fruition
Preferred Qualifications
PhD in a quantitative, informatics, mathematics or analytics domain
Experience using both R and Python to solve business problems
Experience using SAS to build predictive models
Experience building or implementing models using Spark and/or Hadoop
Experience working with medical or pharmacy claims data, electronic medical record data, or other health data
Experience predicting high-variance, continuous dependent variables such as claim cost
Scheduled Weekly Hours

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