Overview
Are you passionate about shaping the future of IBP impacting all business functions at a global scale? Join our team to support global digital developments for PepsiCo, focusing on high-quality demand forecasts and new product forecasting within the Integrated Business Planning program.
As part of an interdisciplinary team, you'll build and deploy statistical/machine learning models, collaborating with process owners, product owners, and business users, ensuring the criticality of your developments is understood.
You will also serve as an internal ambassador, providing expertise and stewardship in data and analytics.
Responsibilities
Your day to day with us:
Partner with data engineers to ensure data access for discovery and proper data is prepared for model consumption.Partner with ML engineers working on industrialization.Coordinate work activities with Business teams, other IT services and as required.Drive the use of the Platform toolset and to also focus on 'the art of the possible' demonstrations to the business as needed.Communicate with business stakeholders in the process of service design, training and knowledge transfer.Support large-scale experimentation and build data-driven 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.Create documentation for learnings and knowledge transfer.Create reusable packages or libraries. Qualifications
What you will need to succeed:
2+ years' experience building solutions in the revenue management or in the supply chain space.2+ years working in a team to deliver production level analytic solutions.Fluent in git (version control).Understanding of Jenkins, Docker are a plus.3+ years' experience in ETL and/or data wrangling techniques.Fluent in SQL syntax.3+ years' experience in Statistical/ML techniques to solve supervised (regression, classification) and unsupervised problems.Experiences with Deep Learning are a plus.3+ years' experience in developing business problem related statistical/ML modeling with industry tools with primary focus on Python or R development.Business storytelling and communicating data insights in business consumable format.Fluent in one Visualization tool.Strong communications and organizational skills with the ability to deal with ambiguity while juggling multiple priorities.Experience with Agile methodology for team work and analytics 'product' creation. Additional qualifications that will make you stand out for this position: Experience with Azure cloud services is a plus.Experience with distributed machine learning is a plus. What makes us different?
Hybrid work model, a 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 PepsiCo
We 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.
#LI-Hybrid #Locations.
Barcelona, Spain; Vitoria-Gasteiz, Spain
#J-18808-Ljbffr
