PepsiCo is looking to implement and support a unified D&Ai products vision and take ownership of analytics components in Supply Chain products, requiring a Data Science SC&Ops Lead to drive effective value-generating Supply Chain practices in D&Ai Data Science.
Requirements
- Deep knowledge of machine learning models and techniques and ability to use them to solve important business challenges.
- Good knowledge of data management, governance, and compliance.
- Good knowledge of modeling and visualization techniques.
- Solid understanding of statistical analysis, descriptive, predictive, and prescriptive modeling.
- Deep understanding of machine learning/AI/GenAI models.
- Ability to run a strong team of Data Scientists and ML engineers.
- Ability to manage multiple Supply Chain projects with competing priorities.
Responsibilities
- Partner with the global D&Ai team to help define the strategic global Supply Chain vision with a focus on applying the right tools in AI, machine learning, and analytics in precise, scalable, secure, and ethical ways.
- Interact with executives across the enterprise to manage the narrative around Data Science and analytics applied to Supply Chain use cases.
- Manage a team capable of creating Data Science components and solving challenging Data Science problems across the enterprise.
- Align with other DS leads on reusable components across initiatives.
- Conceive, plan, and prioritize Data Science and analytics programs and initiatives, consistent with the global D&Ai vision.
- Guide the development of experiments and pilot programs to test new Data Science capabilities in the Supply Chain domain.
- Oversee and report on Data Science work under Supply Chain initiatives.
Other
- Sc. or PhD. in Statistics, Machine Learning, Mathematics, Operations Research, Computer Science, Economics, or any other related quantitative field.
- 7 years+ of working experience in the Supply Chain domain.
- 12 years+ of working experience in a Data Science position, preferably working as a Senior Data Scientist or Enterprise Architect.
- Proven and successful track record of building and leading high-performing Data Science teams.
- Strong organizational and leadership skills.
