Data Science Associate Manager
hace 4 días
Vitoria-Gasteiz
Experteer Overview In this role you lead a high-performing data science team to deliver scalable analytics and ML solutions that support PepsiCo’s Strategy and Transformation agenda. You drive the technical vision, execution, and adoption of data science initiatives, partnering with business and technology leaders to identify high-impact opportunities. You will oversee end-to-end analytics and ML deliveries, including production-ready pipelines and models, while championing a data-driven culture. This role offers the opportunity to shape modern ML workflows, including Generative AI, at scale and across global teams. Compensaciones / Beneficios • Lead, mentor, and grow a team of data scientists with technical guidance and career development • Own end-to-end delivery of large-scale analytics and machine learning initiatives • Define standards and best practices for model development, data pipelines, and ML production workflows • Oversee design, deployment, monitoring, and optimization of ML systems in production • Partner with business stakeholders to translate strategic goals into data science roadmaps and measurable outcomes • Drive adoption of modern techniques, including Generative AI, when delivering clear business value • Communicate technical concepts, progress, and impact to business and technical audiences Responsabilidades • Master's Degree in Data Science, Computer Science, Statistics, or equivalent • 5+ years of experience in data science with leadership or people-management responsibility • Proven experience delivering ML solutions using diverse data sources • Strong Python skills and ability to guide production-quality ML code • Solid understanding of software engineering, data engineering, and MLOps best practices • Experience with deep learning frameworks (TensorFlow or PyTorch) • Strong foundation in statistical and mathematical modeling • Experience with cloud-based and distributed computing platforms • Experience with Generative AI, including LLMs, prompt engineering, and RAG architectures Requisitos principales •