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Senior Data Science Analyst
Senior Data Science AnalystDirect Recruiters • NY, US
Senior Data Science Analyst

Senior Data Science Analyst

Direct Recruiters • NY, US
[job_card.30_days_ago]
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  • [job_card.full_time]
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Job Description

Senior Data Science Analyst

Mount Sinai, one of the leading US health systems with a top-ranked academic medical center, medical school and faculty practice is accelerating a transition to a business model based on population health by launching Mount Sinai Health Partners (MSHP), a new 400+ employee team dedicated to Population Health and Value Based initiatives.

To support these strategies, Health Innovations is partnering with MSHP to recruit a world - class team comprised of talented analysts and data scientists. Specifically, looking for individuals who are passionate about developing a true system of care that creates value for customers and patients.

Position Overview :

The Senior Data Science Analyst will engage with stakeholders from across the organization to develop sophisticated analytics to provide information, insights and BI (Business Intelligence) solutions that contribute to sound strategic planning, decision-making, goal setting, and effective performance measurement. This is senior role that requires advanced understanding of the healthcare domain, technical data manipulation and analytic development skills. The role serves as mentor to others in the Data Science team and takes the lead role in project initiatives.

Education and Experience :

  • BA or BS degree minimum, in a relevant field of study; Master’s degree preferred.
  • 7 years minimum, higher preferred, in analytics development expertise, preferably in health care, or for a health provider, health plan or accountable care organization, including either :
  • Knowledge of the CMS Medicare regulations and related reporting requirements, such as STARS, Risk Adjustment and HEDIS is a strong plus.
  • Experience working in a health plan analytics, actuarial, financial reporting or medical economics department is a strong plus.
  • Clinical experience (RN, MD, DO) a plus.

Technical and Data Science Requirements :

  • Data and database modeling experience is a strong plus.
  • Working knowledge of a health care EMR such as Epic / Clarity, is a plus.
  • Strong data mining skills using tools like SQL, R, Python.
  • Strong analytical skills, with the ability to perform complex analysis and make recommendations based on statistical inferences. Experience with and an understanding of a wide variety of analytical or statistical methods.
  • Strong working knowledge of Business Intelligence products such as Tableau
  • General understanding of ETL tools.
  • Advanced analytical, financial and technical skills needed to perform complex analysis and data modeling using sophisticated report writing and data management tools.
  • Ability to exercise critical thinking and logical reasoning, and understand the conceptual framework and database relationships underlying health care data.
  • Ability to think creatively; demonstrated excellent problem solving skills.
  • Excellent oral and writing skills characterized by the ability to communicate effectively with varying audiences.
  • Demonstrated ability to articulate goals, plan and implement processes to achieve those goals, recognize and assess the implications of confounding variables, anticipate consequences, and meet deadlines.
  • Advanced interpersonal (e.g., mediating, mentoring, teaching) skills required servicing internal and external clients effectively, and managing relationships and activities that are diverse and complex.
  • Self-motivated and resourceful, with a demonstrated ability to think and work independently, and to exercise independent judgment in originating or developing complex techniques or programs in a complex and dynamic environment.
  • High level of integrity as demonstrated by 1) appropriate treatment of confidential or protected health information, 2) adherence to policies, procedures, rules, and regulations, 3) professional conduct in dealing with persons internal and external to the organization, and 4) sensitivity to populations served by the organization.
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