OverviewAre 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.
ResponsibilitiesYour day to day with us Communicate 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.QualificationsWhat you will need to succeed 1+ 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 position Ideally, 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.Professional growth possibilities & learning opportunities.Variety of benefits to support your physical, emotional and financial wellbeing.Volunteering opportunities to help external communities.Diverse team with more than 30% of female representation & over 30 nationalities.Have a stake in D&I strategy and bring your whole self to work.About PepsiCoWe believe that culture should be at the cornerstone of everything we do at PepsiCo. We are agile, innovative and not afraid of failure. We want our team to come to work every day excited to explore new ways to bring enjoyment, refreshment and fun to the world.
PepsiCo Positive (pep+) is the future of our organization – a strategic end-to-end transformation, with sustainability at the center of how we will create growth and value by operating within planetary boundaries and inspiring positive change for the planet and people.
So, if you're ready to be a part of a playground for those who think big, we'd love to chat.
* We encourage the diversity of applicants across gender, age, ethnicity, nationality, sexual orientation, social background, religion or belief and disability.
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#Locations: Barcelona, Spain; Vitoria-Gasteiz, Spain
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