Data Scientist

PepsiCo; Barcelona; Presencial; EUR 50.000 - 70.000; Jornada completa

Descripción de la vacante

A global food and beverage leader based in Barcelona seeks a Data Science Analyst to contribute to digital developments. The role involves leveraging advanced analytics and machine learning, collaborating with interdisciplinary teams, and driving data-driven solutions across various business functions. Candidates should have over 4 years of experience in analytics and ETL processes, with competencies in Python and SQL.

Formación

• 4+ years of experience in building solutions in the commercial or supply chain space.
• 4+ years of delivering production-level analytics solutions.
• Proficient in SQL and ETL processes.

Responsabilidades

• Lead digital projects as a technical expert.
• Create statistical and ML models.
• Collaborate with business and IT teams to ensure project success.

Conocimientos

Analytics solutions

Machine Learning

Communication skills

SQL proficiency

Agile methodologies

Herramientas

Python

SQL

Azure cloud services

Jenkins

Docker

Descripción del empleo

Overview

Your role will be to be part of a growing team based in Barcelona, creating and supporting global digital developments for PepsiCo. As a Data Science Analyst, you will play a pivotal role in leveraging advanced analytics and machine learning to deliver impactful solutions across critical business topics such as Consumer Insights, Revenue Management, Supply Chain, Manufacturing, and Logistics.

You will be part of a collaborative, interdisciplinary team focused on data, responsible for building deployable statistical and machine learning models, from discovery through to implementation. You’ll work closely with process owners, product managers, and end-users to ensure your developments align with business priorities and drive measurable outcomes.

You will serve as an internal ambassador of the team’s data and analytics culture, fostering innovation, collaboration, and data-driven leadership. You will provide guidance to colleagues in your area of expertise, contributing to the team’s growth and success in data and analytics.

Responsibilities

• Contribute as a key member in digital projects, acting as the technical lead.
• Serve as a subject matter expert in specific digital projects.
• Support innovation activities within the team.
• Partner with product managers to translate DS requirements into actionable roadmaps.
• Collaborate with data engineers to ensure data access and proper data preparation for modeling.
• Work with ML engineers to industrialize solutions.
• Engage with Business teams and other IT services as needed.
• Promote the use of the Platform toolset and demonstrate 'the art of the possible' to stakeholders.
• Communicate with business stakeholders during service design, training, and knowledge transfer.
• Support large-scale experimentation and develop data-driven models.
• Define KPIs and metrics to evaluate analytics solutions.
• Refine requirements into modeling problems.
• Influence product teams through data-driven recommendations.
• Research state-of-the-art methodologies.
• Create documentation for learnings and knowledge transfer.
• Assist in developing reusable packages or libraries.

Qualifications

• 4+ years of experience building solutions in the commercial or supply chain space.
• 4+ years of experience in delivering production-level analytics solutions, with proficiency in git. Knowledge of Jenkins and Docker is a plus.
• 4+ years of experience in ETL and data wrangling, with proficiency in SQL.
• 2+ years of experience with statistical and ML techniques for supervised and unsupervised problems; experience with Deep Learning is a plus.
• 2+ years of developing business-related statistical/ML models using industry tools, primarily Python or Scala.
• Ability to communicate insights effectively and storytelling skills, with proficiency in at least one visualization tool.
• Strong organizational skills and ability to handle ambiguity and multiple priorities.
• Experience with Agile methodologies, Jira, and Confluence.
• Proficiency with Azure cloud services is required.
• Additional skills such as Reinforcement Learning, Simulation, Optimization, Bayesian methods, Causal inference, NLP, FAIR data, Responsible AI, and distributed machine learning are considered pluses.