Senior Data Scientist at Humana

Description
Humana's Clinical Analytics and Trend (CAT) Team is seeking a Senior Data Scientist (Remote).
Healthcare is rapidly changing, and our members are living longer, often with more chronic conditions. The Clinical Analytics & Trend team (CAT) identifies clinical saving opportunities and enables clinical solutions through an evidence-based approach using data science, clinical and business expertise, and rigorous study designs to improve health outcomes and lower costs for millions of senior lives. In this multi-disciplinary team, you'll have the opportunity to work closely with decision-marking executives and clinicians to shape Humana's enterprise clinical strategies and initiatives.
The Senior Data Scientist uses statistics, machine learning, business analysis, and technology to transform high volumes of complex data into advanced analytic solutions. The Senior Data Scientists' work assignments involve moderately complex to complex issues where the analysis of situations and data requires an in-depth evaluation of variable factors. The Senior Data Scientist uses statistical and machine learning methods to develop sophisticated models based on large structured and unstructured data set, exercises considerable latitude in determining objectives and approaches to assignments while collaborating closely with clinicians and subject matter experts.
Responsibilities
Responsibilities
As a Senior Data Scientist, you will:
Leverage a wide range of analytics methods ranging from descriptive to prescriptive to transform high volumes of complex data into analytics solutions and actional insights
Work directly with aligned business partners in requirements definition, project scoping, study design, timeline management, results documentation, and maintain effective and professional working relationship
Leverage your curiosity, clinician partnerships, and Humana's data to define and quantify the root causes of poor clinical outcomes
Collaborate with multiple cross-functional teams to identify operational barriers and issues, and facilitate their resolution
Create reusable implementations of statistical tests and machine learning models using the available technologies in Humana's data ecosystem
Required Qualifications
Master's or PhD Degree in a quantitative discipline such as Epidemiology, Economics, Statistics, Data Science, Clinical Informatics, and/or related fields. Clinical degrees also preferred
Experience manipulating and analyzing various types of data using Python, SAS, R, or similar software
Experience using mathematics, statistics, modeling, experimental study design, and technology to transform high volumes of complex data into advanced analytic solutions
Demonstrated ability to assess the impact of clinical interventions on healthcare resource utilization and/or clinical indicators
History of solving problems, creating solutions and driving change within a team
Demonstrated strategic and analytical thinking
Ability to make decisions on moderately complex to complex issues regarding technical approach for project components
Clear and concise oral and written communication skills, with a proven ability to translate complex methodologies and analytical results to higher-level business insights and key takeaways
3 years of professional experience leveraging structured and unstructured healthcare data
Preferred Qualifications
Strong business acumen, including a deep understanding of healthcare payer economics
Experience working with medical, Rx, lab claims to extract clinical information for analytics and modeling purposes
Experience in Big Data environment specifically PySpark, Scala, or Microsoft Azure
Demonstrated familiarity with clinical concepts related to a broad range of clinical conditions and disease states - experience with oncology, behavioral health and chronic conditions would be particularly valuable
Demonstrated familiarity with observational study design and techniques such as retrospective cohorts, cross sectional, propensity score matching, difference-in-differences, etc.
Demonstrated familiarity with statistical tools such as variable selection and supervised/unsupervised ML
Work experience in a health care, health insurance, or consulting setting
Experience working with EMR data
Experience with clinical claims Episode Treatment Groupers
Scheduled Weekly Hours
40
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