Senior Financial Analytics Professional - Medicare Risk Adjustment

Profile

Description

The Senior Financial Analytics Professional designs, builds and operates the tools which develop and deliver financial projections relating to Humana's Medicare business. The Senior Financial Analytics Professional work assignments involve moderately complex to complex issues where the analysis of situations or data requires an in-depth evaluation of variable factors. They include opportunities to influence decisions on day-to-day operations, strategic planning and specific business performance issues.

Responsibilities

In this role you will:


Collaborate with internal data providers and data customers to translate business requirements and features into code
Critically analyze models to explain output variances in terms of changes to inputs or changes in methodology
Produce and deliver financial projections, gathering data from necessary sources
Prepare and present exhibits explaining or substantiating function of the underlying code
Automate and streamline existing projection processes
Make decisions on moderately complex to complex issues regarding technical approach for project components, exercise considerable latitude in determining objectives and approaches to assignments.


Required Qualifications


Bachelor's Degree
5 years technical experience
Experience writing database queries
Basic experience with Python or other high level programming language
Experience in compiling, modeling, interpreting and analyzing data in order to identify, explain, influence variances and trends, and to enhance modeling techniques
Experience working with moderately complex to complex issues where the analysis of situations or data requires an in-depth evaluation of variable factors
Aptitude for problem solving and attention to detail


Preferred Qualifications


Master's Degree
Familiarity with Medicare Advantage payment model
Advanced experience with MS SQL or other dialect - developing stored procedures and relational data structures
Experience with Python and the associated data ecosystem (Pandas, Jupyter, etc)
Financial or actuarial background


Additional Information

Scheduled Weekly Hours

40

Company info

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