Decision Scientist

Become a part of our caring community and help us put health first
 Decision Scientists (Economics and Public Health) support decision making using data and statistical modeling. Their work assignments frequently require crafting complex RCTs and extracting insights about the efficacy of new initiatives. They should therefore be well-versed in experimental design and the analysis of the resulting data.

Pharmacy Analytics and Consulting (PAC) is constantly innovating to enhance our members' experience and maximize our operational efficiency at Humana. Within the Decision Science team, you will be involved in testing our new initiatives using rigorous scientific standards of evaluation. This involves helping to coordinate and design various studies and randomized controlled trails, and working with our business partners to shape their investment decisions based on your findings.

The role sits at the intersection of scientific rigor and practical application and will have a direct impact on the decisions that shape pharmacy over time. The team is therefore instrumental in driving much of the value that our members experience through their pharmacy benefit, increasing their satisfaction, and the sophistication with which the business adapts to changes over time.

You will work with complex data, do statistical hypothesis testing, and create models, as needed. There is also the potential to engage in academic research for broader audiences.

Use your skills to make an impact
 

Required Qualifications

• PhD in economics, public health, statistics, social science, or other relevant discipline
• Knowledge of experimental design and statistical analyses for randomized controlled trials (RCTs)
• 2 or more years of technical experience working with data
• Proficiency in a statistical coding language such as R, or equivalent experience in Python
• Knowledge of SQL
• Ability to communicate technical results to business partners simply and effectively
• Must be passionate about contributing to an organization focused on continuously improving consumer experiences

Preferred Qualifications

• 1 or more years of experience designing and executing RCTs
• Familiarity with observational causal inference methodologies
• Familiarity with Tidyverse in R, SAS, or PySpark

Scheduled Weekly Hours

40

Pay Range

The compensation range below reflects a good faith estimate of starting base pay for full time (40 hours per week) employment at the time of posting. The pay range may be higher or lower based on geographic location and individual pay will vary based on demonstrated job related skills, knowledge, experience, education, certifications, etc.

 

$71,100 - $97,800 per year

 

This job is eligible for a …