GENERAL SUMMARY:
Lead Data Scientist, Healthcare Analytics works with system leaders, business stake holders and business data analysts to fully understand their needs for data science solutions. Lead Data Scientist architects, defines, and design the data science solution, and works with Data Scientist, Associate Data Scientist, and other business analysts to implement the data science solution. Works/collaborates with various teams to build the solution and implement the solution in operations. Lead Data Scientist, Healthcare Analytics develops cutting edge solutions to resolve complex business problems. Skilled in using statistical techniques and good at solution architecting, design and implementing the solution. Hands on in using a variety of common analytical and AI tools. Will present findings in a compelling manner to system leaders, technical and non-technical audience. The position requires a team lead mindset who is ready to lead and deliver the projects using agile methodology.
EDUCATION/EXPERIENCE REQUIRED:
Must have an undergraduate (BS) degree in Statistics, Mathematics, Econometrics, Operations Research, Public Health, and Epidemiology or another related field. Master's degree or PhD degree is preferred. Five plus (5+) years of professional work experience. Three plus (3+) years of experience with predictive, forecasting, and optimization problem solving using data analytics tools like Python, R or SAS.Two plus (2+) years of experience involving quantitative data analyses for problem solving in US Healthcare industry. One plus (1+) year experience working with cloud Big Data Stack to orchestrate data gathering, cleansing, preparation and modelling preferred. Advanced SQL skills working with RDBMSs such as SQL Server, Oracle etc. Exceptionally skilled in machine learning, data analytics, pattern recognition and predictive modelling. Experience working with data visualization tools or Data Visualization Designers in Power BI. Also, experience with data visualization for analytic models in Rshiny, GGPlot, Qlik, Alteryx, Flask, D3, etc. used to tell the data story to business users to foster adoption of analytic outputs created preferred. Strong communication and presentation skills. Effective communication and storytelling skills. Passion for continuous learning and contributing to hands on development. A true team player. Collaborative mindset for effective communication across teams.
