Summary: Performs analysis of complex healthcare and varied data to develop innovations for pressing healthcare delivery challenges through visualization, machine learning, optimization, and statistical inference solutions. Analyzes and models structured data and implements algorithms to support analysis using advanced statistical and mathematical methods from statistics, machine learning, data mining, and predictive modeling. Develops descriptive and predictive models, from conception to completion and provides long-term support. Performs exploratory data analysis, generates and tests working hypotheses, and uncovers interesting trends and relationships. Documents and shares findings in line with scientific best practices for both technical and nontechnical audiences; and understands how to make trade-offs between methods. Key Responsibilities: Data Collection and Cleaning: Collects and cleans data from various sources, ensuring data quality and integrity. Data Analysis: Applies statistical and machine learning techniques to identify patterns, trends, and insights in the data. Model Development: Assists in the development of predictive models, algorithms, and statistical analyses to solve specific business problems. Data Visualization: Creates clear and insightful data visualizations to communicate findings to non-technical stakeholders. Collaboration: Collaborates with cross-functional teams, including clinical subject matter experts, engineers and BI developers, product managers, and business analysts, to provide data-driven solutions. Documentation: Maintains clear and organized documentation of analysis methodologies and results. Continuous Learning: Stays up-to-date with industry trends and emerging data science techniques to improve skills and knowledge.

Education: Master’s degree in a relevant field (e.g., Data Science, Computer Science, Statistics, Mathematics, Engineering) or equivalent. Ph.D. degree preferred.

Licensure/Certification: Epic certification at time of hire or must obtain within 6 months after hire. Formal training in the use of an enterprise analytics software solution. Licensed healthcare professional desirable.

Experience: 3-6 years of relevant work experience in healthcare. Previous experience with Epic Cognitive Computing and Epic certifications. Data modeling experience. Experience with big data technologies (e.g., Hadoop, Spark) preferred. Experience with cloud computing platforms (e.g., AWS, Azure, Google Cloud, and Databricks). Experience with Linux and familiar with concepts of HDA, slate, and docker. Level II Data Scientist is highly skilled across multiple Data Science disciplines. Is able to independently own and solve a well-defined business problem where the solution has not yet been outlined or approach is unclear; is able to provide high quality solutions (e.g., accurate, efficient) which do not require refinement to deliver value; is able to solve difficult problems that require a range of data science methodologies combined with subject matter expertise. Strong analytical and problem-solving skills, and ability to work on moderately complex projects. Proficiency in data analysis and visualization tools (e.g., Python, SQL, Tableau). Familiarity with data warehousing and data integration concepts. Excellent communication skills to convey technical findings to non-technical stakeholders. Strong teamwork and collaboration abilities. Ability to translate business needs into technical specifications. EPIC EMR knowledge is a plus. Demonstrates good customer relations skills. Must be a team player. Skilled at problem solving, strong organization skills, strong attention to detail, and demonstrated ability to understand complex issues and communicate these issues to co-workers. Ability to communicate, both verbally and written, effectively with technical team, as well as managers and end users. Must be available and accessible 24/7/365.