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DescriptionThe 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.ResponsibilitiesAs the Lead Data Scientist, you will collaborate with clinical leaders, program owners, and other analytic resources to set objectives, approaches, and work plans. Specifically, this role will be involved in sizing opportunities to mitigate low value care in the healthcare space. You will research, build, and evaluate new statistical methodologies to assess causal relationships between clinical risk factors and a variety of health outcomes. These findings will be incorporated into the work Humana does to improve the health and wellbeing of Humana's members. You will package your results and communicate them to technical and non-technical business partners and executive decision-makers.ResponsibilitiesInfluence organizational strategy by championing innovative ideas with analytical teams, business partners, and clinicians. You are recognized as a leader who helps drive results for both the analytics organization as well as our business partners.
Support our key business partners within Humana's Enterprise Clinical Management organization to find opportunities to improve health outcomes and lower healthcare costs
Gain trust and respect by measuring, validating and explaining your results, taking ownership of the end-to-end process.
Required QualificationsExperience leading large data science projects, managing requirements across stakeholders to define the analytic approach and technical solutions
Demonstrated ability to handle multiple projects, manage expectations, and deliver results in a fast-paced, dynamic environment
Ability to scope, frame, and deliver data analyses that leverage large datasets including medical claims, pharmacy claims, and/or laboratory results
Demonstrated understanding of advanced statistical methods used to estimate causal relationships in observational data
Demonstrated ability to bring together and combine disparate datasets
Demonstrated ability to develop nuanced study designs that are used to answer specific clinical questions
Clear oral and written communication skills. Experience interpreting and communicating results of complex analyses to technical and non-technical business partners and executive decision makers
4 years of professional experience leveraging large sets of structured and unstructured healthcare data
Preferred QualificationsStrong business acumen, including a deep understanding of healthcare payer economics
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
Master's or PhD Degree in a quantitative discipline such as Economics, Epidemiology, Clinical Informatics, and/or related fields. Clinical degrees or actuarial certifications also preferred.
Experience developing and validating machine learning models and tools
Experience with cloud-based ecosystems (GCP, AWS, Azure, Databricks)
Experience working in Agile environments
Experience working with EMR data
Additional InformationHealthcare is rapidly changing, and our members are living longer, often with more chronic conditions. Consumers expect more personalized and holistic experiences from their health partners. Humana's Enterprise Clinical Operating Model (ECOM), is a multi-year strategy with the goal of improving member experiences and health outcomes through better integrating Humana's processes, technology and clinical capabilities. The person occupying this role will be instrumental in executing on the vision of ECOM in partnership with leaders and teams across Humana.Scheduled Weekly Hours40
