Data Scientist: GenAI & Big Data Impact

Procter & Gamble; Warszawa; On-site; PLN 180,000 - 280,000; Full time

Benefits offered by this job

International team

Career development

Competitive compensation

Training and certifications

Flexible working arrangements

Job summary

Procter & Gamble is expanding its Warsaw Data Science Hub and seeks a passionate Data Scientist to own algorithmic models across multiple business areas. You will work with a 200+ global team, partnering with product and AI teams to scale solutions that impact billions of consumers.

You will build analytics, apply GenAI and classic ML methods, and translate business problems into deployable models while maintaining reliability and impact.

Qualifications

• Master's in a quantitative field or equivalent data science experience.
• At least 2 years of production-grade Data Science experience.
• Cloud infrastructure knowledge: Azure, GCP, Kubernetes.
• Strong coding in Python and Spark.
• Solid SQL, optimization and predictive modelling skills.

Responsibilities

• Partner with product teams and data engineering to understand problems and deploy models.
• Develop insights to steer the algorithmic roadmap in your area of ownership.
• Analyze large datasets and translate behaviors into actionable recommendations.
• Apply ML techniques to answer business questions and propose solutions.
• Develop resilient, production-grade data science pipelines.

Skills

Analytical skills

Leadership

Collaboration

Problem solving

Prioritising

Education

Master's in a quantitative field

Bachelor/Engineer with data science experience

Tools

Python

Spark

SQL

Azure

GCP

Kubernetes

Databricks

BigQuery

PowerBI/Tableau

GitHub/Jira/Confluence

Job description

Procter & Gamble is expanding its Warsaw Data Science Hub and seeks a passionate Data Scientist to own algorithmic models across multiple business areas. You will work with a 200+ global team, partnering with product and AI teams to scale solutions that impact billions of consumers.

You will build analytics, apply GenAI and classic ML methods, and translate business problems into deployable models while maintaining reliability and impact.