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Machine Learning Engineer
hace 3 meses
OverviewThe Integrated Business Planning (IBP) process aims to transform business decision making that will result in profitable and sustainable growth balancing strategic, financial and operational objectives.
It is a cross-functional, rolling planning process integrating product, marketing, sales, supply chain, partner and financial plans into one aligned plan for the business through a global standard.
This single set of numbers will leverage next generation orchestration and analytic technology coupled with data and digital savvy PepsiCo talent, and – in most markets – an enabling decision-support tool, ensuring agile and fast decision- making to take us to the next level above the competition.
You will be part of a growing team to create and support global digital developments for PepsiCo around topics related with Finance Management, Revenue Management, Supply Chain, Manufacturing, Logistics.
You will be part of a collaborative interdisciplinary team around data, where?you will?be responsible of building deployable statistical/machine learning models, starting from the discovery phase.
You will work with process owners, product owners and final business users.As a member of the Data Science team, you will explore and analyze data coming from a wide variety of sources (both internal and external) to attain a deep understanding of it, both from data science and from a business perspective.
This will enable you to create accurate forecasting models as well as to explain the insights of the results obtained to the business stakeholders.
Responsibilities- Explore and analyze data to gain powerful insights, both from a data science as from a business perspective
- Create, evaluate, compare and improve forecasting models to attain a business-grade AI forecast
- Integrate your forecasting models into the existing DataOps/MLOps environment so that they are scalable, robust and production-ready
- Explain your findings and conclusions both to a Data Science audience as well as to a business audience.
- Integrate into a multidisciplinary team, collaborate with other members to improve the overall team efficiency and results
- Supervise the models in production to detect failures or performance issues and debug them if needed
- Create and maintain documentation for insights and knowledge transfer
- Research and apply novel technologies that may improve the existing processes Qualifications
- Building complete solutions in machine learning, including data exploration, feature engineering, model design and evaluation, and deployment in production
- Statistical/ML techniques and concepts.
- Experience with Azure and/or DataBricks is a big plus
- Experience with time series forecasting is a plus
- Business storytelling and communicating data insights in business consumable format
- Agile methodology for team work and analytics 'product' creation
- Great communication skills, both to technical and to business audiences
- Capacity to work in a complex project, with many stakeholders involved in different stages of the system
- Must feel comfortable working inside a team, with frequent collaborative sessions
- Capacity to plan, to prioritize goals and to define and enforce limits to the time and effort required to achieve an objective
- Ability to work and set a roadmap when dealing with new problems for which the solution is not clear beforehand and some exploration and trial and error is requiredAbout PepsiCoWe believe that culture should be at the cornerstone of everything we do at PepsiCo.
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#LI-Hybrid#Locations: Barcelona, Spain; Vitoria-Gasteiz, Spain