Senior Data Scientist (Supply Chain Planning)

Co będziesz robić

Job Location

WARSAW - EU SUPPLY NETWORK HUB

Job Description

Within our Demand Planning team, we forecast how much of our everyday essentials (like diapers, laundry detergents, disinfectants, soap or shampoos) our retail customers will order - helping P&G stay ready to meet that demand wherever and whenever it arises. We’re looking for an ambitious Senior Data Scientist who thrives in high-impact environments, builds ML models, transforms them into production-ready pipelines, and understands the balance between technical excellence and business relevance. You’ll be joining a global organization with strong data maturity, where you’ll shape scalable solutions across forecasting, optimization, and applied analytics domains.

What You’ll Do:

• Design, develop, and deploy demand-forecasting models for the full product lifecycle (from product launch through discontinuation)
• Advance our forecasting engines with techniques such as time-series clustering and statistical/ML modeling (scikit-learn, stats models)
• Lead initiatives on feature engineering, model evaluation, and forecast-accuracy monitoring at scale
• Build and maintain robust, config-driven data pipelines using Databricks and PySpark
• Collaborate with cross-functional teams on end-to-end solution delivery — from prototype to production
• Contribute to our internal forecasting library and advocate for clean architecture, modular design, and long-term maintainability
• Lead cross functional teams and support management with a data-driven decision making

Who we are

P&G was founded over 180 years ago as a simple soap and candle company. Today, we’re the world’s largest consumer goods company and home to iconic, trusted brands that make life a little bit easier in small but meaningful ways. We’ve spanned three centuries thanks to three simple ideas: leadership, innovation and citizenship. The insight, innovation and passion of hardworking teams has helped us grow into a global company that is governed responsibly and ethically, that is open and transparent, and that supports good causes and protects the environment. This is a place where you can be proud to work and do something that matters.

Wymagania

Job Qualifications

• Solid Data Science background in areas of: Time Series forecasting, Supervised learning, and ML/statistical algorithms (scikit-learn, statsmodels)
• Strong Python programming skills, with hands-on experience across the scientific stack (pandas, NumPy, SciPy)
• Experience turning models into production-ready, modular pipelines with clean architecture and config-driven design (e.g. Pydantic)
• Proficiency with version control (Git)
• At least 4 years of experience as a Data Scientist or a related position (Data Engineer / Software Engineer / AI Engineer / ML Ops)
• Excellent collaboration skills and working comfortably within a cross-functional team
• Shown success in leadership, problem solving and priority setting
• English proficiency and at least a Bachelor's degree

Nice to have:

• Experience building distributed data pipelines with PySpark on Databricks, and familiarity with SQL and Azure
• Exposure to demand/sales forecasting, product-lifecycle modeling, or forecast-accuracy evaluation
• Prior background knowledge of Supply Chain or FMCG domains

Co oferujemy

What we offer

• Work in an international Data Science team with global responsibilities (with large part of engineering and product teams located in Warsaw)
• Long-term career with development and growth opportunities
• Competitive salary and benefits program (private health care, life insurance, P&G stock options, saving plans, lunch subsidy, sport cards, in-office fitness center)
• Relevant trainings, certifications, conference participation
• Internal coaching programs & training
• Flexible working arrangements
• At Procter & Gamble, we embrace a hybrid work model that combines the flexibility of remote work with the collaborative benefits of in-office engagement. Employees can enjoy the option to work from home two days a week while also spending time in the office to foster teamwork and enhance communication.