The Data Science Manager is responsible for leading a full array of analytics, clinical analytic consulting and applied analytic activities at WellMed. This individual is responsible for the development and delivery of large and complex predictive modeling and advanced analytics projects.
Develops innovative and effective approaches to solve WellMed's analytic needs and communicates results and methodologies. Provides directions and guidelines to the data science team members to discover business insights, identify opportunities, and provide solutions and recommendations to solve business problems through the use of statistical, algorithmic, data mining and visualization techniques.
In addition to advanced analytic skills, the Data Science Manager is also proficient at integrating and preparing large, varied datasets, architecting specialized database and computing environments, and communicating results.
- Work closely with Chief Medical Informatics Officer (CMIO) and business stakeholders to drive predictive modeling and advanced analytics projects
- Design predictive modeling and data mining approaches, based on quality, utilization and cost data, to support consistent delivery of cost effective, high quality care initiatives that can drive value for our patients
- Design sampling methodology, prepare data, including data cleaning, univariate analysis, missing value imputation, etc., identify appropriate analytic and statistical methodology, develop predictive models and document process and results
- Develop the approach for integration of new and existing provider performance data into comprehensive analytic evaluation tools
- Provide on-going tracking and monitoring of performance of statistical models and recommend ongoing improvements to methods and algorithms that lead to findings, including new information
- Responsible for clinical report development and presentation of findings, including identification of actionable insights related to WellMed's value in terms of patient care, clinical quality, and cost outcomes
- Apply advanced statistical and predictive modeling techniques to build, maintain, and improve on multiple predictive detection engines
- Lead or support the development of clinical analytic approaches, draft analytic approaches, evaluate clinical value, and lead the interpretation and positioning of analytic findings and value
- Summarize, communicate, and/or present analytics results and predictive model findings; adjusting the content and level of detail to appropriate audience (executives, market leadership, providers/clinics, business partners, etc.)
- Provide consultative support to clinicians, data stewards, business and technology leaders
- Conduct training and educational programs in data science
- Lead the data science team to discover insights and identify opportunities through the use of statistical, data mining and visualization techniques
- Oversee multiple projects at the same time, meeting deadlines as agreed upon with our development and project partners
- Coordinate and manage the data science team's daily activities supporting the business and technical teams
- Develop and mentor the data science team by setting team direction, resolving problems and providing guidance
- Perform all other related duties as assigned
To be considered for this position, applicants need to meet the qualifications listed in this posting. Required Qualifications:
- Bachelors in a related field such as Information Technology/Computer Science, Mathematics/Statistics, Analytics, Economics, Business Technology, or similar quantitative fields of study
- 5+ years of statistical analysis, quantitative analytics, and/or forecasting/predicting analytics
- 5+ years hands on data analysis, business intelligence, or application development
- 5+ years of experience manipulating large datasets and using databases
- 5+ years hands-on predictive modeling and data visualization experience
- Experience using at least one programming language (R, SAS, or Python) for analysis
- Experience using supervised and unsupervised learning methods to derive practical analytic insights
- Working knowledge of healthcare administrative data (medical claims, enrollment, provider data) or clinical data systems (electronic medical records, hospital monitoring systems, etc.)
- Experience leading projects, ensuring deliverable quality, tracking progress, and reporting status
- Experience with small group facilitation, conducting formal presentations, and with written and verbal communications with senior leadership or customers
- Supervisory experience; preferably in a technology or healthcare organization
- Microsoft Office Products experience (Excel, Word, Visio and Power Point)
- Master's or Ph.D. degree in statistics, applied statistics, applied mathematics, economics, or similar quantitative fields of study
- Knowledge and process experience using systems development life cycle (SDLC) for advanced analytics implementations and support for predictive analytics models
- Big data experience (Hive, Spark, HDFS)
- Hands on ability to expertly use query languages including SQL (Hive or PIG a plus)
- Understanding of machine-learning techniques and algorithms such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
- Knowledge of clustering, classification techniques, and optimization algorithms
- User Interface (UI) design experience for automated and-or end-user-interactive visualizations, displays or reports based on the models
- Experience with business intelligence tools such as Tableau, Power BI, Qlik, etc.
- Experience with Tableau