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Data Scientist 2
  • Python
  • SQL
  • SAS
  • Machine Learning
  • Modeling
  • Business Analysis
  • Azure
Humana
Louisville, KY
160 days ago

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.

Responsibilities

Humana is seeking a Data Scientist 2 that will support the Part D Analytics team. The role is analytic in nature, and requires an in depth understanding of coding and data to be successful. The Data Scientist 2 will be working with Actuaries and Pharmacists on a day to day basis, with some interaction and exposure to senior leadership.

Key responsibilities include:

  • Creating reports, projections, models, and presentations to support business strategy and tactics.
  • Developing, maintaining, and collecting (structured and unstructured) data sets for analysis and reporting.
  • Understanding department, segment, and organizational strategy and operating objectives, including their linkages to related areas.
  • Makes decisions regarding own work, requires minimal direction, and receives guidance where needed. Follows established guidelines/procedures.
  • Self-motivated to question the status quo and help design solutions and model enhancements.
  • Maintaining SAS/R/Python code along with creating new enhancements to streamline Part D trend forecasts
  • Develop improvements to existing processes and models
  • Provide periodic forecast updates alongside drivers of actual to expected variance

In the first year this role will focus on the following:

Improving and understanding the current drug-level utilization model (R and SAS) and further developing techniques used to forecast Part D claims. Possible improvements include:

  • Collaboration with actuaries on team to streamline forecast and review of current processes
  • Identify areas for improvement in current forecast methodology
  • Assist in transitioning models to cloud computing environments where necessary
  • Develop new processes and models which can be leveraged to forecast Part D claims. Examples include:
    • Regression/Machine Learning models to predict “time to next fill”
    • State transition models to predict when a member transitions to a new/additional condition
    • Scenario modeling used to quantify the risk associated with various pricing strategies


Required Qualifications

  • Bachelor’s Degree with 3-4 years of data science, statistical and/or analytical experience or:
  • Master’s Degree with 1-2 years of data science, statistical and/or analytical experience
  • Demonstrated experience coding in SQL, Python, R and/or SAS
  • Ability to use data to drive business outcomes and decisions

Preferred Qualifications

  • Advanced Degree
  • Advanced Python and/or SQL knowledge
  • Experience working with Azure, AWS, or other cloud computing service
  • Healthcare experience

Scheduled Weekly Hours

40

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