The Data Scientist 2 uses mathematics, statistics, modeling, business analysis, and technology to transform high volumes of complex data into advanced analytic solutions. The Data Scientist 2 work assignments are varied and frequently require interpretation and independent determination of the appropriate courses of action.
You will play a role in helping the broader Humana organization understand how leveraging data will transform us from a health insurer to a provider of life-long well-being. You will be part of Humana’s Consumer Science group and work to:
Participate in discussions with the internal business partners to determine areas of challenge that are opportunities for analytics to be the right tool
Develop analytical constructs based on addressing business challenges
Perform exploratory data analysis, statistical modeling, machine learning and insights generation in areas related to consumer health and well-being
Combine and analyze diverse types of data to extract fresh, actionable discoveries about our members and their healthcare and health-related behavior
Develop machine learning to drive acquisition, retention, loyalty, wellness, consumer engagement, satisfaction and sustainable measureable health related behavior change
Participate in developing and selecting new data sources and ensuring the quality and reliability of the data
Measure and communicate the effect of models in production
Develop test designs for campaigns and communications leveraging Design of Experiments (DoE) concepts
Provide data-driven support of sales efforts
Develop innovative approaches for allowing consumer data to contribute to price-elasticity models and new-product development
Develop processes and criteria for analyzing and summarizing data
Participate in relationships with Humana’s external partners
Master degree in a quantitative field (Statistics, Business Analytics, Mathematics, Operations Research, Engineering, Data Science) and 1+ years technical experience
Working knowledge and experience in at least one of the statistical analysis packages SAS, Python, R
Experience in building machine learning models(Regression, Decision Tree, Random Forest, Neural Networks, etc)
Experience in data mining, statistics, analytical methods and tools, techniques and algorithms
Experience in Design of Experiments
Strong communication skills with ability to convey complex ideas efficiently
PhD in a quantitative field (Statistics, Business Analytics, Mathematics, Operations Research, Engineering, Data Science)
Experience in Structured Query Language (SQL)
Experience in programming language (Hadoop, Hive, Java, Scala etc.)
Working knowledge/ Experience in Big Data tools is a plus
Experience in data visualization such as Tableau
Experience with health care data
Scheduled Weekly Hours
Equal Opportunity Employer
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