Informatics Analyst - ESS

Profile

Description

ESS Business Intelligence is an Enterprise Shared Services team focused on data, reporting and data science supporting Humana's Service Operations. The team is focused on converting data to actionable insights for our business partners who can utilize to reduce administrative cost and improve the customer's experience.

This position will work within the Advanced Analytics team, as part of the broader ESS Business Intelligence organization. This team is focused on Data Science, Data Consulting, and Data Visualization.

Responsibilities

The Informatics Analyst utilizes advanced analytics techniques to solve business problems. Working closely with Senior Data Scientists, the Informatics Analyst synthesizes data from multiple sources using advanced data wrangling techniques to prepare data for predictive models. Writes complex database queries and translates data collected into clear and concise insights. Understands how to effectively structure data for different kinds of analyses. Understands the data science pipeline and works with subject matter experts to engineer useful features for models. Effectively communicates insights generated to a wide range of business stakeholders. Makes decisions regarding own work methods, occasionally in ambiguous situations, and requires minimal direction and receives guidance where needed.

Required Qualifications


Bachelor's degree
2 - 5 years of data analysis experience
Proven experience working with complex data sets within large organizations, preferably healthcare
Intermediate to advanced skills pulling and manipulating large and complex datasets using SQL required
Experience with Python and associated analytics libraries
Proficiency with Excel for data exploration & analysis
Ability to use appropriate problem solving, research and analysis tools
Experience with data mining, predictive modeling techniques and using data to drive business outcomes and decisions
Strong attention to detail
Excellent written and verbal communication
Must be passionate about contributing to an organization focused on continuously improving consumer experiences


Preferred Qualifications


Advanced Degree
Coursework in data science, machine learning, advanced data mining
Exposure to cloud data platforms: Hadoop, Azure, etc.


Scheduled Weekly Hours

40

Company info

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