Senior Data Scientist - Remote
Humana

Job Info

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Description

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

Humana's Clinical Trend and Analytics Team is seeking a Senior Data Scientist (Remote).

The Clinical Trend and Analytics team leverages advanced scientific techniques, forecasting, and machine learning to predict financial and clinical outcomes in order to guide investments that improve health outcomes and reduce costs. In this exciting start-up environment, you'll have the opportunity to develop data science processes from the ground up and work directly with decision-making executives to shape the future of Humana's most important strategic 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

As a Senior Data Scientist, you will:

• Use techniques from statistical analysis, causal inference modeling, and/or supervised and unsupervised machine learning to deliver business insights and analytics solutions
  
• Work directly with aligned business partners in requirements definition, project scoping, study design, timeline management, results documentation, and maintain effective and professional working relationship
  
• Work with clinicians to create definitions for medical diagnoses, medical treatments, and/or clinical interventions from healthcare data
  
• Leverage your curiosity, clinician partnerships, and Humana's data to define and quantify the root causes of poor clinical outcomes
  
• Create reusable implementations of statistical tests and machine learning models using the available technologies in Humana's data ecosystem
  
• Use causal inference techniques to size potential opportunities for interventions and assess outcomes of existing interventions and clinical programs
  
• Collaborate with multiple cross-functional teams to identify operational barriers and issues, and facilitate their resolution
  

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
• 3 years of professional experience manipulating and analyzing various types of healthcare data using Python, SAS, R, or similar software
• Ability to transform broad clinical and business queries into articulated analytic questions, and solve them using statistical models and/or machine learning techniques
• Experience in working with assignments that involve moderately complex to complex issues where the analysis of situations or data requires an in-depth evaluation of variable factors
• Demonstrated strategic and analytical thinking
• Experience in creating reports, projections, models, and presentations to support business strategy and tactics
• 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

Preferred Qualifications

• Demonstrated good understanding of causal inference concepts and techniques such as propensity score matching, regression discontinuity, difference in differences, double machine learning, doubly robust learning, and instrumental variables
• Experience using causal inference packages in Python or R such as EconML, Dowhy, and CausalML
• Experience working with medical, Rx, lab claims to extract clinical information for analytics and modeling purposes
• Experience with Spark and building end-to-end modeling pipeline using PySpark, Spark ML, Scala, or similar tools in Azure Cloud environment
• Demonstrated deep understanding of statistical tools such as variable selection and supervised/unsupervised ML
• Work experience in a health care, insurance or consulting setting
• Strong business acumen, including a deep understanding of healthcare payer economics

Additional Information

Scheduled Weekly Hours

40

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