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Humana Senior Data Scientist in Portsmouth, New Hampshire


The Senior Data Scientist uses mathematics, 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 epidemiological and machine learning methods to develop sophisticated models based on large structured and unstructured data set. The Senior Data Scientist exercises considerable latitude in determining objectives and approaches to assignments while collaborating closely with clinicians and subject matter experts.



As a Senior Data Scientist, you will:

  • Work directly with aligned business partners in requirements definition, project scoping, 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

  • Experience manipulating and analyzing various types of data using Python, SAS, R, or similar software

  • Experience using epidemiological methods, 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

  • 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

  • Ability to make decisions on moderately complex to complex issues regarding technical approach for project components

  • 3 years of professional experience leveraging structured and unstructured claims data

Preferred Qualifications

  • Strong business acumen, including a deep understanding of healthcare payer economics

  • Master's or PhD Degree in a quantitative discipline such as Economics, Epidemiology, Clinical Informatics, Statistics, and/or related fields. Clinical degrees also preferred

  • Demonstrated familiarity with clinical concepts related to a broad range of clinical conditions and disease states - experience with oncology and chronic conditions would be particularly valuable

  • Experience developing and validating machine learning models

  • Work experience in a health care, insurance or consulting setting

  • Experience in Big Data environment specifically PySpark, Scala, or Microsoft Azure

Scheduled Weekly Hours