Data Privacy Data Scientist - Data Governance Office at Humana Studio_h
The Data Governance Office at Humana is looking for a candidate who has both statistical analysis and regulatory compliance skills and a passion for data to help us tell a compelling story about modern healthcare. Through the design and implementation of appropriate data de-identification processes and the strategic interpretation of data, we provide Humana and our external clients with meaningful, real-life insights about healthcare utilization and costs, patterns of treatment use, health outcomes, disease burden, and more.
We are dedicated to the pursuit of analyzing diverse types of primary and secondary data to extract new, actionable discoveries about our members and their health-related behaviors. While ensuring regulatory compliance, we encourage our associates to research and use their experience to continue to grow our capabilities that will build knowledge and innovation in the service of our members through data democratization. We’re looking for driven, innovative candidates who are interested in using their skills to help Humana make lasting, positive changes in the healthcare industry through technology and research.
The Data Privacy Data Scientist will work cross-functionally and collaboratively with teams throughout Humana to guide research and ensure we represent the privacy of our clients by removing identifying information from data sets. Acting as a data scientist, this individual would:
- Use their statistical and data science skills to evaluate data de-identification using the expert determination method under HIPAA
- Monitoring the creation of synthetic data, including specifying appropriate virtual machine architectures in cloud environments for a given generation engagement
- Support the development of new end-to-end processes and optimization of existing ones which relate to the protection of data
- Participate in additional enterprise risk and governance processes as necessary
First Year Success Factors
- You have determined the risk of re-identification, in accordance with HIPAA guidelines, of multiple de-identified data sets
- You have validated the models created in the course of synthetic data generation to ensure that the created data is an appropriate extrapolation of the relationships within the data
- You have cultivated relationships with internal business partners and senior leadership
- Masters and/or PhD in Data Science, Analytics, or Statistics
- Experience in synthetic data generation tools (GPU based VMs, python/TensorFlow, Torch, etc. . .), methods, and architectures
- Experience with analytics and research studies
- Experience with synthetic data generation tools, methods, and architectures
- Experience in working on problems of diverse scope and complexity in a collaborative fashion
- Ability to present complex analysis results tailored to the necessary audiences in a highly consumable and actionable form
- Excellent oral and written skills.
- Familiarity with analytics and reporting tools and techniques
- Ability to exercise independent judgment and decision making on complex issues
- 2-5 years in healthcare or other highly regulated industries.
- Experience working within the bounds and requirements of HIPAA
- Demonstrable and proven competence in developing data or research strategies and in performing data analysis, modeling, and outcomes research
- Experience utilizing de-identification platforms such as Delphix or Privacy Analytics’ Eclipse
- Ability to execute work in a matrixed environment with little delay.