Humana Data Scientist 2 in United States


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

Required Qualifications

  • 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

Preferred Qualifications

  • 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


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