**About Nestlé Health Science**
Nestlé Health Science is a globally recognized leader in the science of nutrition, with more than 11,000 employees around the world. We are redefining the management of health through our portfolio of science-based consumer health, medical nutrition, vitamin and supplement brands, and pharmaceutical therapies.
**Position Overview**
The NHSc Global Data Science Lead will design, develop, and deploy statistics-based algorithmic solutions to address business questions. This role involves supervising or contributing to the collection, analysis, and interpretation of large data sets. Formulating testing strategies and validating hypotheses will be a key part of your role. You will collaborate with Data Engineers to industrialize solutions and provide critical insights to senior stakeholders, promoting data literacy.
**Responsibilities**
* Contribute to the Global Data & Analytics roadmap.
* Identify business needs and design new methodologies to address unique business questions.
* Determine data requirements for training and developing models.
* Supervise and mentor the data science team from a scientific and methodological perspective.
* Validate mathematical acceptability, business credibility, and testing methodology for all data science and machine learning projects.
* Develop models, perform analysis, and present results in a concise, executive-ready manner.
* Manage teams in data science to execute the roadmap.
* Identify opportunities to optimize investments and deployments across markets, coordinating with stakeholders.
* Lead and supervise external collaborators, ensuring high standards and quality delivery.
**Requirements**
* Master's Degree or PhD (preferred) in a quantitative field.
* 5+ years of data science experience, with at least 2 years managing teams.
* Proven delivery of impactful data science projects in a business setting.
* Expertise in Commercial Analytics, including Marketing Mix Modeling, with deep knowledge of eCommerce, promotion, and pricing analytics.
* Proficiency in Python, SQL, and bash (PySpark is a plus).
* Strong proficiency in machine learning, statistics, and experimental design.
* Familiarity with cloud platforms and big data technologies.
* Ability to work in a global and cross-functional environment, collaborating with teams across regions and business units.
* Excellent communication skills for technical and non-technical audiences.