Strategic Data Scientist at McKesson analyzing data for healthcare products and customer success. Responsible for insights that drive product recommendations and improve client profitability.
Responsibilities
Serve as the lead analytics point of contact for specific Biopharma customers.
Frequently develops data and storytelling to help anticipate and meet the strategic needs of a customer and Customer Success Team (CST).
Develop trusted advisor relationships with key accounts, customer stakeholders and executive sponsors.
Work closely with Commercial Customer Success Team (CST) members and external clients, demonstrating the value of CMM products through data narratives.
Perform in-depth analyses to identify opportunities which can lead to recommendations to improve overall profitability, value or strategic use of our products.
Responsibilities will include using and identifying patient, product and network models to interpret data, creating ad-hoc reports, data visualizations, and modifying and updating standard reports when applicable.
Lead new data-driven insight presentations with customers.
Use creative means to proactively identify areas of improvement to enhance product value for clients.
Monitor portfolio programs to support continuous quality improvement efforts using performance metric development and monitoring, and effectively communicate to this to stakeholders via strategic business reviews, scheduled meetings or where require appropriate escalation.
Perform in-depth analysis to identify key business risks and opportunities and make recommendations to improve overall profitability and value.
Requirements
Bachelor’s degree in Data Science, Statistics, Computer Science, Engineering, Public Health Information, Bioinformatics, or a related quantitative field, or equivalent practical experience
3-5 years of experience in a role in healthcare/Pharma industry or similar
Understanding of data science methodologies including decision trees, multivariate analysis, segmentation modeling, factor analysis, regression analysis, forecasting, machine learning, etc.
Experience with statistical software experience (PYTHON, R, MATLAB, SAS, etc.) is a plus
Curious problem solver by nature; able to quickly make sense of complex data issues.
Driven, self-motivated, team player adept at working in environment with competing priorities.
Experience with data mining, analysis, and providing insights.
Adept at creating queries, writing reports, and presenting findings.
Intermediate to Advanced proficiency in SQL.
Intermediate to Advanced proficiency in data visualization tools e.g., Excel, Tableau, Power BI etc.
Excellent communication and presentation skills including to senior leadership and C-Suite external stakeholders; able to “think on your feet” and respond to questions where the answer is not known or not straightforward.
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