Senior Healthcare Data Scientist

The successful candidate will have experience with Machine Learning/AI, Statistics and Operations Research and a passion for working with healthcare data. Previous experience with various computational approaches along with an ability to demonstrate a portfolio of relevant prior projects is essential. II. Principal Responsibilities and Tasks • Support and drive analytic efforts designed around the organizations strategic priorities and clinical/business problems. • Develop and manage predictive (machine learning and deep learning) and prescriptive (mathematical optimization and simulation) analytic models in support of the organizations clinical, operations and business initiatives and priorities. • Deploy solutions so that they provide actionable insights to the organization and are embedded or integrated with application systems. • Work with the analytics team and clinical/business stakeholders to develop pilots so that they may be tested and validated in pilot/incubator settings. • Perform statistical analysis to evaluate primary and secondary objectives from such pilots. • Develop strategic, tactical and operational presentations that summarize the results of predictive and prescriptive analytics projects in support of robust strategies for the organization. • Build and extend our analytics portfolio supported by robust documentation. • Lead cross-functional design teams to drive disruptive innovation, which may translate into improved quality of care, clinical outcomes, reduced costs, temporal efficiencies and process improvements. • Manage projects and initiatives for the medical system that include multi-disciplinary teams from technology, clinical and business groups. • Mentor staff on effective problem-solving strategies and technical aspects of Machine Learning/AI, Statistics and Operations Research. • Manage project plans and other required project documentation and provide updates to leadership as necessary. • Develop and maintain relationships with business, IT and clinical leaders and stakeholders across the enterprise to facilitate collaboration and effective communication. • Assist senior leadership with strategies for scaling successful projects across the organization, and enhance the analytics applications based on feedback from end-users and clinical/business consumers. • Assist senior leadership with dissemination of success stories (and failures) in an effort to increase analytics literacy and adoption across the organization. • Work with autonomy to find solutions to complex problems using open source tools and in-house development. • Stay abreast of state-of-the-art literature in the fields of machine learning/AI, operations research, statistical modeling, statistical process control and mathematical optimization. III. Education and Experience PhD degree in applied mathematics, data science, physics, computer science, engineering, statistics, economics, or a closely related field required; comparable work experience may be substituted for the PhD degree. 7+ years of industry experience in the following: • Machine Learning/AI, Statistics or Operations Research. Programming with SQL, Python and R. • Practical experience with machine learning/AI problems, or formulating and solving mathematical (deterministic and stochastic) optimization problems and simulation, or performing advanced statistical analysis. • Developing and applying computational algorithms and statistical methods to healthcare data (including, but not limited to data from electronic medical record, financial management, human resources, quality and supply chain). • Developing and deploying healthcare-relevant predictive and prescriptive models. • Combining analytic methods and advanced data visualizations. • Text mining and Natural Language Processing (NLP) is preferred. • Leading and managing projects and multi-disciplinary teams. IV. Knowledge, Skills And Abilities • Develop (from scratch) machine learning and/or deep learning approaches and algorithms to solve clinical and business (including operations, supply chain, human resources, finance) problems. • Formulate and solve complex mathematical optimization problems using exact and heuristic approaches. • Perform independent/unsupervised exploratory data analysis and advanced statistical analysis (e.g., regression analysis, cluster analysis, factor analysis, ANOVA). • Design and prototype new application functionality for our products. • Work with real world data including scrubbing, transformation, and imputation. • Capable of artful storytelling and clearly presenting findings in oral and written format and through graphics to stakeholders at various organization levels. • Knowledge of databases, data structures, data processing and data mining from large enterprise transaction systems (e.g., Epic, Infor/Lawson, McKesson HPM, Payer Claims or similar applications in healthcare or other industries). • Effective at working independently and in collaboration with other staff members for software platform and web application development. • Cooperatively and effectively work with people from various organization levels. • Manage projects and cross-functional teams to meet organizational goals. • Plan work, set clear direction, and coordinate own tasks as well as project teams tasks in a fast-paced multidisciplinary environment, including triaging issues, identifying data anomalies, and debugging software. • Able to compare, contrast, and validate work with keen attention to detail. • Actively generate process improvements; support and drive change, and confront difficult circumstances in creative ways.