BACKGROUND - CANOPY HEALTH

 

-        Canopy Health, formed in 2015 with leadership from UCSF and John Muir Health (JMH) and with participation from additional, leading Bay Area providers, is creating an integrated healthcare experience where quality care and coverage are provided by an alliance of the top caregivers across the Bay area, allowing people to access the best options for their personal needs. Owned by physicians and hospitals, Canopy Health is a community of caregivers championing health. Our focus is on improving health, advocating for the entire Bay Area, and supporting individuals in a way that is empathetic and respectful. Our large network of physicians and other providers will offer consistently high-quality care with clear, foreseeable costs.  

 

-        Founded in 2015, BayHealth Development is a University of California San Francisco Health (UCSF) and John Muir Health (JMH) joint venture company focused on infrastructure development supporting the needs of the Canopy Health accountable care network, and serving as a joint strategic investment vehicle in support of the UCSF/JMH affiliation. BayHealth Development is deeply committed to value creation in the Canopy Health network and our shared vision with UCSF/JMH for innovation in patient experience, access, affordability and quality of care.

 

 

ORGANIZATION

-        This position reports to the CFO of Canopy Health and BayHealth Development. This position will work with senior business leaders in both organizations and will interact with the health plan, provider and vendor partners.

-        The Data Scientist will be a strategic partner of Canopy Health and BayHealth finance leadership team. The Data Scientist will work with finance leadership to develop leading practice finance and actuarial capabilities to support the achievement of the strategic goals of Canopy Health and Bayhealth.

 

KEY RESPONSIBILITIES

-        Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.

-        Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.

-        Assess the effectiveness and accuracy of new data sources and data gathering techniques.

-        Develop custom data models and algorithms to apply to data sets.

-        Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.

-        Develop company testing framework and test model quality.

-        Coordinate with different functional teams to implement models and monitor outcomes.-        Develop custom data models and algorithms to apply to data sets.

-        Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.

-        Develop company testing framework and test model quality.

-        Coordinate with different functional teams to implement models and monitor outcomes.

Develop processes and tools to monitor and analyze model performance and data accuracy.


Education/License:

-        Master’s or PHD in Statistics, Mathematics, Computer Science or another quantitative field-        Requires deep knowledge of healthcare economics obtained through professional experience and advanced education

-        Experience:

-        Requires deep knowledge of healthcare economics obtained through professional experience and advanced education

-        Typically viewed as a specialist within the Data Science area and may have basic knowledge of project management

-        Requires a minimum of 2 to 3 years of professional experience for one or more healthcare organizations (health plan, integrated health system / complex hospital, large IPA, ACO, healthcare company).

-        5-7 years of experience manipulating data sets and building statistical models and is familiar with the following software/tools:

o   Knowledge and experience in statistical and data mining techniques: GLM/Regression, Decision Trees, Random Forests, Support Vector Machines, Boosting, text mining, social network analysis, etc.

o   Experience querying databases and using statistical computer languages: R, Python, SQL, Julia, etc.

o   Experience using web services: Redshift, S3, Spark, DigitalOcean, etc.

o   Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.

o   Experience analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, etc.

o   Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.

o   Experience visualizing/presenting data for stakeholders using: Periscope, Tableau, Business Objects, D3, ggplot


Knowledge/Skills Required:

-        Strong problem solving skills with an emphasis on product development.

-        Experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.

-        Experience working with and creating data architectures.

-        Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.

-        Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.

-        Excellent written and verbal communication skills for coordinating across teams.

-        A drive to learn and master new technologies and techniques.