Provides technical direction, including both strategic and tactical planning, execution and support of strategies for the SCPMG Medical informatics group. The position entails developing machine learning approaches to address healthcare's triple aim: to improve the health of populations, to lower the cost of care, and enhance the care experience.
- Design, develop, and evaluate state-of-the-art machine learning models for complex, large-scale data sets.
- Use statistical and machine learning techniques to provide clinical decision support as well as improve auditing and standards of care workflows.
- Deliver insights and values from heterogeneous data to investigate complex problems in the health care domain for multiple use cases.
- Use machine learning, statistical and programming skills to enable data analytics.
- Drive informed decision-making and present findings to both technical and non-technical audiences.
- Work closely with physicians to identify medically relevant use cases, develop machine learning models, and validate impact
- Provide technical direction and mentor junior members of the Medical Informatics team.
- Work closely with software engineers to facilitate model integration and deployment
- Embrace a fast paced, collaborative environment dedicated to building atop cutting-edge technology.
- Minimum five (5) years of experience in architecting and building scalable distributed systems, working in a fast-paced multidisciplinary environment, advocating innovative uses for data, including methodologies, techniques, and tools, working with Software Development Life Cycle (SDLC) and leading from conceptualization to production stage large-scale applications.
- Master's degree (MS) in computer science or related fields
License, Certification, Registration
- Experience with deep learning frameworks: e.g. Tensorflow, PyTorch.
- Knowledge of classification and regression algorithms
- Experience with Deep Learning approaches to Natural Language Understanding (NLU) and Language Modeling.
- Experience with time series analysis, discrete data modeling and feature engineering.
- Expert knowledge of Python
- Experience with SQL
- Experience with Java/C++
- Experience with machine learning continuous integration and deployment
- Experience with Tensorflow Serving
- Doctorate degree in computer science or related fields
- Knowledge of healthcare terminology
PrimaryLocation : California,San Diego,El Camino Real Administration
HoursPerWeek : 40
Shift : Day
Workdays : Mon, Tue, Wed, Thu, Fri
WorkingHoursStart : 08:00 AM
WorkingHoursEnd : 04:30 PM
Job Schedule : Full-time
Job Type : Standard
Employee Status : Regular
Employee Group/Union Affiliation : NUE-SCAL-01|NUE|Non Union Employee
Job Level : Individual Contributor
Job Category : Information Technology
Department : Parsons West Annex - Prj Mgmt-Innovtn Proj-Qlty&Svc - 0806
Travel : Yes, 10 % of the Time
Kaiser Permanente is an equal opportunity employer committed to a diverse and inclusive workforce. Applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy), age, sexual orientation, national origin, marital status, parental status, ancestry, disability, gender identity, veteran status, genetic information, other distinguishing characteristics of diversity and inclusion, or any other protected status.
External hires must pass a background check/drug screen. Qualified applicants with arrest and/or conviction records will be considered for employment in a manner consistent with federal and state laws, as well as applicable local ordinances, including but not limited to the San Francisco and Los Angeles Fair Chance Ordinances.