AI/ML Data Scientist II
The AI/ML Data Scientist II is responsible for building Data Science, Machine Learning (ML), and Predictive Analytics solutions for enabling value-based healthcare, population health management, and enterprise analytics. Identifies, conceptualizes, designs, builds, operationalizes, and manages Data Science, Machine Learning, and Advanced Analytics solutions to drive business actions that promote population health management and integrated care delivery. Collaborates closely with clinical and administrative stakeholders in Pediatric Associates and Alpine Physician Partners.
ESSENTIAL DUTIES AND RESPONSIBILITIES
This list may not include all of the duties that may be assigned.
- Manages predictive analytics solutions that support critical business workflows for value-based and integrated care delivery, such as care management and care coordination.
- Identifies, conceptualizes, designs, builds, operationalizes, and manages Data Science, Machine Learning, and Predictive Analytics solutions using cloud-based AI/ML (Artificial Intelligence / Machine Learning) technology stack, including Databricks Data Science and Machine Learning and Azure AI/ML platforms.
- Applies Data Science and Machine Learning for building robust predictive models to surface actionable insights. Applies predictive modeling techniques and algorithms, including supervised machine learning, unsupervised machine learning, recommender systems, and statistical models.
- Deploys, automates, maintains, and manages cloud-based Machine Learning solutions such as MLOps to ensure the availability, performance, scalability, and security of production systems.
- Collaborates with data engineers, cloud platform engineers, data analysts, and other technical team members to leverage data pipelines, distributed data processing, and the cloud data and analytics platform capabilities to deliver robust predictive analytics solutions.
- Partners with clinical and administrative leaders to plan, deploy, and operationalize predictive models for population health management business actions, including care coordination, care management, patient activation, patient engagement, and performance management.
- Engages with cross-functional stakeholders to identify pain points, business and technical requirements, and to design analytics solutions using best-practice patterns and modern architecture.
EDUCATION: Minimum BA or BS degree in Computer Science, Statistics, or related field required. MS in Business Analytics, Computer Science or related discipline highly preferred.
EXPERIENCE: Minimum 3 years of experience in creating enterprise-grade predictive advanced and Machine Learning solutions using Cloud AI/ML technology stack, such as Databricks AI/ML Technology Stack and Azure Cloud Services required, 4-5 years preferred.
KNOWLEDGE, SKILLS AND ABILITIES
- High proficiency in Python and/or R programming for building Machine Learning models.
- Highly skilled in understanding and applying classical and deep learning Machine Learning algorithms (Regression, Classification, Clustering, etc.) and common libraries (e.g., MLib, Scikit-Learn, Tensorflow, PyTorch, XGBoost).
- Skilled in applying structured Data Science/Machine Learning model development process (CRISP-DM) for planning, building, and operationalizing predictive analytics solutions to drive business actions and business outcomes.
- High proficiency in distributed data (structured, semi-structured, unstructured, streaming) processing techniques using Apache Spark, Hadoop, Hive, Kafka, and big data ecosystem technologies.
- Ability to influence decisions related to advanced analytics strategy and roadmaps, business use cases, and analytics platform capabilities.
- Effective communication and collaboration with internal cross functional teams, leadership team, technology partners and vendors, and end users.
- Excellent analytical and organizational skills with ability to work in a startup environment.
- Ability to deliver on tight deadlines using Agile practices.
- Healthcare industry experience highly desired.
TYPICAL WORKING CONDITIONS
- Non-patient facing
- May be either full time remote/telework or rotate working in the office and remote/telework
- If remote, this job must be U.S. based
- Indoor work; professional office environment
- Operating computer
- Reach outward
OTHER PHYSICAL REQUIREMENTS
- Sense of sound
- Sense of touch
Adhere to all organizational information security policies and protect all sensitive information including but not limited to ePHI and PHI (Protected Health Information) in accordance with organizational policy, Federal, State, and local regulations.