Senior Data Scientist

Overview

Your role will be based in Vitoria-Gasteiz (Hybrid) to make key contributions to AI projects with a primary focus on computer vision, alongside natural language processing, foundational models and other general AI / ML solutions aligned with PEP AI roadmap within the global digital transformation journey within PepsiCo.

You will be part of a collaborative interdisciplinary team around data and analytics, where you will explore new technologies, and design the adoption of new products in the domain of computer vision AI to support the development of digital solutions to create business decision making. Your work will span retail analytics, quality control systems, supply chain optimization, and consumer insights through visual intelligence. On the one hand, you will work closely with process owners, product owners and final business users. This will provide you the correct visibility and understanding of criticality of your developments to business stakeholders and S&T functional leaders. On the other hand, you will work closely with other data scientists to transfer your findings to ensure the scalability, robustness and reusability of the solutions that you develop.

You will be an internal ambassador of the team's culture around data and analytics. You will provide stewardship to colleagues in the solution development landscape and further lead the onboarding of new developments in AI within the PepsiCo domain leading the development of best practices and standard ways of working.

Responsibilities

• Active contributor to code development in projects and services related to computer vision, object detection, image segmentation, video analytics, machine learning, mathematical modeling, AI and ML / AI Operations, and deep learning.
• Design and deploy CV models for real-world applications including retail execution monitoring, manufacturing quality control, supply chain optimization, and visual search.
• Active contributor in innovation activities, exploring the boundaries of technology to create AI solutions with the ability to continually prove accuracy and with a design goal of productization / reusability.
• Create documentation for learnings and knowledge transfer.
• Create reusable packages or libraries.
• Partner with data engineers to ensure data access for discovery and proper data is prepared for model consumption.
• Partner with other data scientists working on industrialization.
• Occasionally, coordinate work activities with business teams, other services and as required.
• Communicate with data scientists and other S&T stakeholders in the process of service design, training and knowledge transfer.
• Support large-scale experimentation and build analytical models.
• Set KPIs and metrics to evaluate analytics solution given a particular use case.
• Refine requirements into modelling problems.
• Influence product teams through data-based recommendations.
• Research in state-of-the-art methodologies.

Qualifications