Overview: Are you ready to shape the future of data and drive global business growth?
Join PepsiCo's Global Data, Analytics AI team as a Data Product Manager for Commercial and Consumer Products.
In this pivotal role, you'll be at the forefront of our Data Product Management team, responsible for articulating the vision and leading the implementation of PepsiCo's next-generation global data infrastructure.
You will oversee the full Strategy Transformation agenda and drive all Data Product roadmap initiatives.
As a Data Product Manager, you will lead the delivery of sDNA—an advanced suite of data products and data science models focused on driving PepsiCo's sales growth.
By leveraging a granular understanding of retail outlets and consumer data, you'll play a crucial role in transforming our data into actionable insights that power our business strategies.
If you're passionate about data innovation and strategic impact, we want you to join us!
Responsibilities: Your day-to-day with us: Define and Execute Roadmap: Develop and deliver the vision and strategy for Store DNA, a complex product spanning 15+ global markets, aiming for end-to-end automation of the sDNA ecosystem.
Product Delivery Ownership: Manage overall product delivery, including cost estimation, timeline management, and resource allocation within an Agile framework.
Partner with Key Tech Teams: Work closely with Data Engineering and Data Science to deploy the product in new markets, drive continuous improvements, and address user feedback.
Agile Project Management: Enable roadmap delivery through SAFe Agile Project Management using ADO, ensuring efficient and effective execution.
Operationalize Deployments: Streamline sDNA deployments to enhance engagement with local markets and optimize operational processes.
Data Landscape Improvement: Continuously enhance our data landscape by sourcing and evaluating relevant data.
Vendor Management: Manage, evaluate, and negotiate with existing and prospective data vendors to ensure high-quality data solutions.
Vision Evangelism: Articulate and advocate the product vision across the business, acting as a change agent for PepsiCo's digitization agenda through workshops, demos, presentations, and one-on-one sessions.
Translate Vision into Requirements: Convert the product vision into concrete feature requirements, user stories, and technical data requirements, in collaboration with Data Engineering and Data Science.
Customer Acceptance: Define and drive Business Customer acceptance criteria for delivery from Data Analytics.
Insight Translation: Act as a bridge between Data Science analytics and business end users to ensure the delivery of actionable insights.
Prioritization: Balance different market and project needs by prioritizing requests and initiatives while aiming to build standardized and generalizable solutions.
Manage Related Products: Oversee secondary and interrelated products, including dependent data science models and front-end dashboards.
Integration and Alignment: Stay informed about other PepsiCo digital initiatives to identify future integration opportunities and align with product roadmaps.
Advocate Modern Practices: Promote modern data and product management practices, such as Data Mesh, MLOps, active metadata, user-centric design, and design thinking, both within and outside the team.
Qualifications: What will you need to succeed?
We are seeking a professional with 10+ years of overall technology experience that includes at least: 3+ years of Product Management experience.
2+ years of experience leading/building advanced analytics and big data solutions.
8+ years of experience in Data Analytics, Data Modeling, Data Science or Data Management in business-facing functions.
2+ years of experience in Food/Beverage/Manufacturing or Consumer Products industry (will be a plus).
Experience, and a passion for, turning ad hoc data deliverables into scalable products.
Excellent ability to identify sources of value from data analytics across consumer and customer business domains.
Familiarity with Azure Cloud services, Data Analytics products, and data governance principles.
Passion about Agility DevOps and bringing it to life in a large organization in a pragmatic manner.
Understanding of fundamental machine-learning principles (for instance, training versus predicting, performance measurement, and overfit), as well as techniques such as random forests or neural networks.
Familiarity with machine-learning technologies and tools, such as big data stack, Python, and visualization techniques.
Strong communication skills and an ability to break down complex information into relevant and digestible points for both inside DAi and externally to the business.
Excellent leadership skills, with a team-player attitude to drive the end-to-end implementation of use cases under time pressure.
Advanced English skills are necessary.
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