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McKinsey Solutions – HSS Analytics – Senior Analyst (MATLAB) – AP – Gurgaon

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Description


 Overview
McKinsey & Company (McKinsey) is a global management consulting firm that advises the world’s leading businesses, governments and institutions. McKinsey has more than 100 offices in over 60 countries and serves eight out of the ten of Fortune Magazine’s Most Admired Companies.
Detailed Description
McKinsey & Company is a global management consulting firm that advises the world’s leading businesses, governments and institutions. With more than 100 offices in over 60 countries, we have a truly global reach and serve more than eight in ten of Fortune magazine’s Most Admired Companies.  We have created a dedicated group in our healthcare practice called   Healthcare System & Services – Analytics (HSS-A). HSS-A designs, delivers and operates advanced analytics, models and algorithms powering healthcare payment innovation. Our team is divided into 8 domains covering different aspects of the US healthcare industry. The domains are Episode-Based Payment Models, Population Health Payment Models, Special Need Populations, Market Insights, Provider Performance & Improvement, Provider Growth, Payment Integrity & Risk Coding, and Healthcare Data Management. 
Role:
The Analyst will be responsible for working with statisticians, actuaries, experts and consultants to understand the client’s requirements, to design and to develop intelligent solutions using US Health Insurance databases.

Industry:  Healthcare
 Main Responsibilities:
  • Understanding business requirements from domain manager, statisticians, experts and consultants, to independently work with them to develop, maintain and augment McKinsey’s propriety solution MPACT
  • Independently drive analytic workstream/solution modules and play leadership role in releasing them for production
  • Integrate advanced actuarial modelling, analytic and quantitative tools, statistical modelling techniques, and data mining procedures and tools to derive business insights, solve complex business problems and improve decisions
  • Understand health insurance data structures of client and external data sources to conduct quality checks and formalize validation rules to ensure the data is complete and accurate
  • Acquire deep understanding of US Healthcare domain
  • Problem solve and propose solutions depending upon given constraints
  • Engage in regular problem solving sessions with overall leadership and analytic team leadership to present findings and refine their own analytic plan
  • Develop actuarial and/or statistical models for client to use to improve decision making in key business processes (e.g., product development, pricing, and marketing).
  • Contribute positively to a dynamic team of analysts with skills including consumer marketing, risk, advanced statistical and/or actuarial analytics
  • Coordinate with other analysts and with leadership to develop sustainable and reproducible IP that can be applied across clients and markets
  • Perform data integration, manipulation, validation and querying for purposes of reporting and more sophisticated analytics
  • Present complex information in an understandable and compelling manner
  • Deliver end products/solutions maintaining quick turn around times and highest quality standards
  • Enhance the existing modelling process to attain better efficiencies
Desired Skills
Qualifications:
  • Post Graduate/Graduate in Statistics or MBA from reputed institute, and having a course in mathematics/statistics is a plus
  • Formal MATLAB academic course during Graduation/Post Graduation.
  • Thorough understanding and application of statistical techniques in real world business environment
  • Exceptional academic qualifications including advanced statistical training, consumer marketing and/or risk analytics. Experience in independently executing advanced analytics with practical business output (e.g., statistical, data and ideally actuarial) to drive business results
       To find out more information about the role and to apply, please click here

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