Data Scientist

PepsiCo; Almería; Presencial; EUR 45.000 - 65.000; Jornada completa

Descripción de la vacante

A leading global food and beverage company is seeking a Data Science Analyst in Almería. This role involves leveraging analytics and machine learning to develop impactful solutions, leading digital projects, and collaborating with cross-functional teams. The ideal candidate has extensive experience in delivering production-level analytics, proficiency in data wrangling, and strong communication skills. This is a full-time position with opportunities for growth and mentorship.

Formación

• 4+ years in commercial or supply chain analytics solutions.
• Experience with production-level analytics and git.
• 2+ years with statistical and ML techniques.

Responsabilidades

• Lead digital projects and act as a subject matter expert.
• Collaborate with product managers and data engineers.
• Promote platform tools and guide stakeholders.

Conocimientos

Analytics solutions delivery

Machine learning techniques

Statistical modeling

Data wrangling

Communication skills

Agile methodologies

Herramientas

Python

SQL

Azure

Docker

Jira

Confluence

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 leverage advanced analytics and machine learning to deliver impactful solutions across key business areas 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 will 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 for the team's culture around data and analytics, fostering innovation, collaboration, and data-driven leadership. You will also provide mentorship to colleagues, contributing to the team's growth and success in data and analytics.

Responsibilities

• Lead digital projects as a technical lead.
• Act as a subject matter expert in digital projects.
• Support innovation activities within the team.
• Partner with product managers to translate DS requirements into roadmaps.
• Collaborate with data engineers to ensure data accessibility and quality for modeling.
• Work with ML engineers to industrialize solutions.
• Engage with Business teams and other IT services as needed.
• Promote the use of Platform tools 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.
• Translate business requirements into modeling problems.
• Influence product teams with data-driven recommendations.
• Research state-of-the-art methodologies.
• Create documentation for knowledge transfer.
• Develop reusable packages or libraries.

Qualifications

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