Lead Data Scientist

Humana

Lead Data Scientist

R-241932

Description

The Lead Data Scientist uses mathematics, statistics, modeling, business analysis, and technology to transform high volumes of complex data into advanced analytic solutions. The Lead Data Scientist works on problems of diverse scope and complexity ranging from moderate to substantial.

Responsibilities

The Clinical Trend and Analytics team leverage 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 Humanas most important strategic initiatives.

As the Lead Data Scientist, you will collaborate with clinical leaders, program owners, and other analytic resources to set objectives, approaches, and work plans. 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 Humanas members. You will package your results and communicate them to technical and non-technical business partners and executive decision-makers.

Responsibilities

• Influence 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 Humanas 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

Required Qualifications

• Experience 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 a 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 Qualifications

• Strong 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
• Masters or PhD Degree in a quantitative discipline such as Economics, Epidemiology, Clinical Informatics, and/or related fields. Clinical degrees 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 Information

• Scheduled Weekly Hours 40