Lead Data Scientist - Hybrid, Data-Driven ML Leader

PepsiCo; Vitoria; Hybrid; EUR 55,000 - 90,000; Full time

Benefits offered by this job

Hybrid work model

Entrepreneurial environment

Professional growth

Benefits package

Volunteering opportunities

Job summary

PepsiCo is expanding its Global Digital Commerce Team to power International Growth and reinvent our data capabilities. We’re seeking seasoned data scientists to build deployable ML models, starting from discovery, working with product owners and data engineers to deliver insights that drive business decisions.

You will participate in an interdisciplinary team, contribute to scalable analytics, evaluate modeling approaches, and create reusable code and documentation to share learnings across

Qualifications

• 4+ years delivering production level analytic solutions.
• 4+ years’ experience in ETL and/or data wrangling techniques.
• 4+ years’ experience in Statistical/ML techniques (supervised/unsupervised).
• 4+ years’ experience in Python or Scala development for modeling.
• Experience with distributed ML is a plus.
• Experience with Jira/Confluence for analytics product creation.

Responsibilities

• Develop deployable statistical and ML models from discovery through production.
• Collaborate with data engineers and product owners to ensure data readiness for modeling.
• Contribute to code development and best practices in a world class analytics team.
• Support large-scale experiments and define KPIs to evaluate analytics solutions.
• Document learnings and create reusable libraries for knowledge transfer.

Skills

Git

SQL

Python/Scala

ML modeling

Deep Learning

Data wrangling

Visualization

Agile

Jira/Confluence

PySpark/SQL

Tools

Docker

Jenkins

Kubernetes

Job description

PepsiCo is expanding its Global Digital Commerce Team to power International Growth and reinvent our data capabilities. We’re seeking seasoned data scientists to build deployable ML models, starting from discovery, working with product owners and data engineers to deliver insights that drive business decisions.

You will participate in an interdisciplinary team, contribute to scalable analytics, evaluate modeling approaches, and create reusable code and documentation to share learnings across