.Overview Are you ready to drive PepsiCo's digital evolution and accelerate transformation across our global operations?As part of the Analytics stream of the Global Agro Digital Transformation initiative, this role will support the development of analytics use cases for Agro, mostly in the data exploration and visualization, and the modeling of agricultural processes (crop modeling, storage modeling). In this role you will be in charge of generating insights from agronomic data, in order to provide recommendations to maximize the agricultural production of supplies in a sustainable way and with good quality.Responsibilities Your day to day with usCommunicate with business stakeholders in the process of service design, training and knowledge transfer.Day-to-day guidance of a small team of data scientists, aligning priorities and solutions with the project lead.Generate insights from agronomic data, in order to provide recommendations to maximize the agricultural production of supplies in a sustainable way and with good quality.Ensure data access for discovery and proper data is prepared for model usage partnering with data engineers.Generate analytics pipelines and dashboards to refresh and share results for main use cases, including geo-spatial information, to enable stakeholders to have access to main results.Support large-scale experimentation and build data-driven models.Deploy reusable models and recommendations engines to different regions, with proper localization to its particularities.Research in methodologies to fine tune the approach for every analytics use case, with the validation of leads.Generate reusable packages or libraries, with proper documentation.Qualifications What you will need to succeed1+ years' of technical lead/coordination of a team of data scientists.2+ years' client/stakeholder facing experience, to collect requirements/specifications, present results and gather feedback.4+ years' experience building solutions in the revenue management or in the supply chain space.4+ years working in a team to deliver production level analytic solutions - Fluent in git (version control).4+ years' experience in ETL and/or data wrangling techniques - Fluent in SQL syntax.4+ years' experience in Statistical/ML techniques to solve supervised (regression, classification) and unsupervised problems.3+ years' experience in developing business problem related statistical/ML modeling with industry tools with primary focus on Python or pyspark development.Experience with MLOps framework design and building machine learning pipelines.Knowledge of containerization technology (Docker/Kubernetes) and REST API design.Additional qualifications that will make you stand out for this positionIdeally, experience with MLflow.What makes us different? Hybrid work model: combination of remote and collaborative office experience to enable innovation.Entrepreneurial environment in leading international company
