Data Science Manager

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The role is to join a growing team based in the United States (preferably in Plano, Texas) to create and support global digital initiatives for Pepsi Co under the SC&Ops umbrella. These initiatives will focus on one or more of the following areas:
Manufacturing, Warehousing and Transportation.

You will be part of a collaborative interdisciplinary team around data, where you will be responsible for building deployable statistical/machine learning models, starting from the discovery phase. You will work closely with process owners, product owners and final business users, gaining visibility and understanding of the criticality of your developments. You will also be an internal ambassador of the team’s culture around data and analytics, providing stewardship to colleagues in the areas that you are a specialist or you are specializing.

• Develop a sustainable analytical toolkit in the form of reusable libraries or components that can be deployed through configuration for specific projects and datasets.
• Manage requests coming from various market-specific teams through data-driven prioritization by keeping the long-term product vision in mind.
• Be able to work in Azure and Databricks environments, but be prepared to switch to other platforms.
• Partner with data engineers to ensure data readiness and accessibility for model consumption.
• Coordinate work activities with business teams, other IT services and other teams, if required.
• Drive the use of the platform toolset and focus on ‘the art of the possible’ demonstrations to the business as needed.
• Communicate with business stakeholders in the process of service design, training and knowledge transfer.
• Support large‑scale hypothesis testing and build data‑driven models.
• Set KPIs and metrics to evaluate analytics solutions given a particular use case.
• Translate requirements into modelling problems.
• Influence product teams through data-based recommendations.
• Research and bring to practice state-of-the-art methodologies.
• Create documentation for learnings and knowledge transfer.
• Create reusable packages or libraries.

• The expected compensation range for this position is between $106,400 - $178,100.
• Location, confirmed job-related skills, experience, and education will be considered in setting actual starting salary. Your recruiter can share more about the specific salary range during the hiring process.
• Bonus based on performance and eligibility target payout is 12% of annual salary paid out annually. Qualifications
  • 7+ years’ experience designing and deploying solutions in revenue management, supply chain, or related operations domains.
  • 5+ years working collaboratively within a team to deliver production‑grade analytic solutions. Fluent with version control (Git) and containerization (Docker).
  • 7+ years’ experience with ETL pipelines and data wrangling techniques; fluent in SQL syntax and database query optimization.
  • 7+ years’ experience applying statistical and machine learning techniques to solve supervised (regression, classification) and unsupervised learning problems; experience with deep learning and foundational models is a plus.
  • 7+ years’ experience developing business‑relevant statistical or machine learning models using industry‑standard tools, with primary focus on Python or Scala.
  • 7+ years’ experience in developing business problem related statistical/ML modeling with industry tools with primary focus on Python or Scala development.
  • Demonstrated experience applying simulation and optimization methods to solve complex business or operational problems.
  • Strong business storytelling and ability to communicate data insights in a clear, actionable format for business stakeholders.
  • Strong communication and organizational skills with the ability to manage ambiguity and balance multiple priorities. Hands‑on experience with Agile methodologies for teamwork and analytics product development; fluent in Jira and Confluence.
  • Practical experience with Azure cloud services is essential.
  • Experience with Reinforcement Learning is a plus.
  • Experience with Computer Vision is a plus.
  • Exper…