5 - 7 years
Posted 81 days ago
The Senior Data Scientist position develops predictive and prescriptive models based on large-scale datasets to address various business problems through leveraging advanced statistical modeling, operations research, machine learning, or data mining techniques. The Data Scientist will work with other staff in developing demand models, capacity management models, physician supply and demand studies, layout efficiency/optimization analyses, process simulation assessments, financial analysis, and strategic planning for outpatient practices of Mayo Clinic across the enterprise. This position also be responsible to gather, analyze, present findings to leadership. The Data Scientist will provide develop the analytics tools that can be used by other staff with non-technical expertise. Specific duties include: designs experiments, create hypotheses, conduct statistical analyses and build models to drive insights and strategic recommendations; applies advanced statistical and optimization modeling techniques to build, maintain, and improve on multiple real time decision systems; models and frames business scenarios that are meaningful and which impact on critical business processes and/or decisions; leads discovery processes with Institute stakeholders to identify the business requirements and the expected outcome; develops innovative and effective approaches to solve client's analytics problems and communicates results and methodologies; makes strategic recommendations on data collection, integration and retention requirements incorporating business requirements and knowledge of best practices; automating models and metrics that track product performance; integrates analytics with other disciplines to support initiatives, research, and project requirements; communicates insights to key stakeholders, which include technical and non-technical audiences (must be able to understand, interpret and convey technical information to others); demonstrated project management skills, including working with a diverse team, managing budgets, milestones, and schedules; independently manages multiple medium or single institution scale projects of mild to moderate complexity through the entire project life cycle. Identifies, translates and applies best practices on assigned projects; provides mentoring to engineers and other junior data scientists as appropriate with some guidance from leadership.
Master's degree in management, industrial engineering, statistics, economics systems engineering, operations research, analytics is preferred. If Master's degree: 5 years of relevant experience. If a Doctorate degree: 3 years of relevant experience. Experience in a similar role involving consulting, operations research, statistical modeling, operations analysis, data analytics workflow analysis, staffing analysis, process engineering. Experience using advanced engineering techniques, including operational research, queuing analysis, theory of constraints and simulation. Expected level of experience in software programming using OR packages, simulation, R, Python or SAS, and other data mining tools. Additional
PhD. in industrial engineering, systems engineering, statistics, operations research, business administration. Understanding of health care industry, and associated key performance drivers, business trends, and the latest industry developments in Qualitative, Quantitative and advanced engineering analysis. Demonstrated project management skills, including working with a diverse team, managing budgets, milestones, and schedules. Certified Analytics Professional (CAP) is encouraged.