Détails du poste

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve – we care.

What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow’s health today, we want to hear from you.

The Lead Data Scientist, Operations Research role is responsible for architecting and implementing AI/ML, simulation and/or optimization products to enhance the efficiency and effectiveness of McKesson’s supply chain operations as part of a McKesson’s Supply Chain Operations Research COE.

Our team applies data science methodologies to interdisciplinary business problems across Operations & Supply Chain. This position will primarily work on strategic in-flight use cases around inventory and operating expense management. The position’s objectives are:

• Develop stochastic process models and/or optimization models to provide data-driven recommendations to business unit stakeholders
• Lead development and enhancement of enterprise-scale digital twins for network management and control

The candidate should possess the ability to perform statistical modelling techniques and derive business insights that are required to drive analytic innovation at McKesson. The candidate should also be an active learner able to grasp and apply new analytic approaches, as well as mentor junior / developing resources.

Position Description

The purpose of this position is to architect, implement, drive adoption, and measure impact of innovative analytic solutions at McKesson, as well as make significant improvements to existing solutions.

Analytic Responsibilities

• Develop supply chain network design, inventory, and/or transportation cost optimization solutions
• Develop statistical simulation decision frameworks
• Development of AI/ML-based solutions and enhancements where needed in support of simulation and optimization workstreams

Other Responsibilities

• Support stakeholders’ analytic needs, gather user requirements, and help drive adoption of developed methodologies
• Cultivate business development opportunities
• Assist in developing and maintaining long-term stakeholder relationships

Education:

Bachelor’s degree in technical fields such as Operations Research, Statistics, Computer Science, Applied Mathematics, Engineering or related quantitative majors. Master's and/or PhD preferred.

Minimum Requirements

• A degree or equivalent and typically requires 10+ years of relevant experience. Fewer years required if they have relevant Master’s or Doctorate qualifications

Critical Skills

• 7+ years of operations research/data science experience based on a combination of industry and academic experience
• Demonstrated experience with solving enterprise network design, inventory, and/or transportation optimization problems
• Experience with Gurobi, Xpress, CPLEX or open-source solvers (CBC, GLPK)
• Experience with local search techniques and advanced mathematical programming techniques such as column generation and decomposition.
• Knowledge of statistical programming (Python or R)
• Fundamental statistical knowledge (i.e., random variables, probability distributions, confidence intervals, outlier detection)
• Experience with Monte Carlo simulation
• Demonstrated ability in data extraction and wrangling using SQL
• Ability to communicate technical concepts to non-technical audiences

Additional Knowledge & Skills

• Team player
• Strong verbal and written communication
• Proficient with Excel spreadsheets, financial modeling, and reporting
• Knowledge of relational databases (e.g. MS SQL Server, Snowflake, Oracle)
• Knowledge of data warehousing & ETL best practices is a plus
• Knowledge of cloud computing platforms (e.g. Azure, AWS, Databricks) is a plus
• Prior data mining experience using enterprise systems (SAP or JD Edwards preferred) is a plus

Please note that only candidates authorized to work in the US will be considered for this position. Sponsorship is not available.

We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here.

Our Base Pay Range for this position

McKesson is an Equal Opportunity Employer

McKesson provides equal employment opportunities to applicants and employees and is committed to a diverse and inclusive environment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age or genetic information. For additional information on McKesson’s full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page.

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