Senior Data Scientist, Clinical Analytics
Plano, TX, United States
The Data & Analytics team is a multi-disciplinary team of Actuaries, Data Analysts, Data Scientists, and Data Engineers with a passion of using data and advanced analytics to solve business problems and to support Collective Health’s strategy and business objectives. We are responsible for developing data products, generating performance metrics, projecting and monitoring medical cost trends, supporting client’s information needs, generating predictive and ML modeling, and conducting inferential studies.
The Senior Data Scientist role is critical to our data-driven decision making processes for the organization and other data & analytics stakeholders. You will master our varied types of data from healthcare claims data, digital engagement data, product performance data, and operational data. You will also design and execute statistical and analytical methodologies for estimating ROI and quantifying business opportunities. You will have a meaningful role with high visibility across the company and the opportunity to mentor and collaborate with others.
What you will Do:
Establish a data-driven product development culture by driving the definition, tracking, and operationalizing of product metrics and increasing data accessibility.
Turn open ended business questions and data into concise, insightful analysis and recommendations.
Build internal tools to increase productivity and scale our data science capabilities using Python.
Conduct analysis to identify opportunities to improve population health, to reduce medical cost, and to inform clinical strategy
Quantify intervention based cost savings based on human and digital outreach to members
Support an ROI analysis for our Utilization Management and Care Navigation programs
Develop and execute measurement methodology to assess the cost savings and ROI for clinical programs, including, but not limit to, utilization management program, care management program, steerage, and digital outreach to members.
Develop predictive models to identify high risk populations for clinical interventions.
Stay up-to-date on the latest trends and best practices in healthcare analytics and cost optimization
What you will bring:
Three years of experience in analyzing health care claims data in a health care payer setting.
Two years of experience in conducting inferential studies to assess the effectiveness and cost impact of clinical programs, such as care management or utilization management programs to improve plan spend.
Experience with application of code sets and industry standards to healthcare data.
Ability to create compelling visualizations including dashboards of utilization and care interventions data to communicate trends and insights effectively.
Strong statistical knowledge (regression, experimental design, hypothesis testing)
Strong quantitative programming skills in python and database skills using SQL
Two years of experience in developing predictive risk models using health care data.
Strong quantitative programming skills in python and database skills using SQL, along with software development best practices.
Demonstrated ability to translate business problems into analyses using appropriate methods and models with Python and SQL.
Ability to communicate findings into a wide range of audiences at different levels.
Master’s or PhD in a Quantitative field.
Pay Transparency Statement
This is a hybrid position based out of our offices: San Francisco, CA, Plano, TX, or Lehi, UT, with the expectation of being in office at least three weekdays per week. #LI-hybrid
The actual pay rate offered within the range will depend on factors including geographic location, qualifications, experience, and internal equity. In addition to the salary, you will be eligible for stock options and benefits like health insurance, 401k, and paid time off. Learn more about our benefits at https://jobs.collectivehealth.com/#benefits .
#J-18808-Ljbffr