Data Scientist Master's degree (2025 Grads)

Position Overview

At P&G, our goal is to empower the business with algorithms that augment every important business decision by providing outstanding insights from models. As a Data Scientist for P&G, you will drive efficiency and impact our business results across multiple platforms.

Examples of specialized roles include:

• As a Media and Marketing Data Scientist, you will apply the predictive power of algorithms to maximize returns and optimize P&G media spend.
• As a Digital Commerce Data Scientist, you will leverage modeling methodologies in the e-retail environment, harnessing big data to grow our digital sales through partnerships with leading global retailers.
• As a Supply Chain Data Scientist, you will use optimization and simulation techniques to refine and streamline our manufacturing and supply chain.
• As a Model Risk Officer, you will collaborate with other Data Scientists to improve and validate models to ensure they are future-proofed.

Key Responsibilities

• Lead cross-functional teams of Data Scientists, Data Engineers, and Software Developers from hypothesis formation to the finished product.
• Partner with IT functions and Business Leaders to build strategy, develop roadmaps, and communicate effectively with company leadership.
• Build and manage an impactful Data Science team, driving the professional development of team members.
• Apply technical and business expertise to feature engineering, exploratory data analysis, and model building to deliver accurate and actionable insights.
• Translate analytic insights into concrete recommendations for business or product improvements.
• Quantify improvements in business areas resulting from the use of algorithms and modeling.
• Exhibit a self-motivated attitude with the ability to balance multiple priorities, coupled with a strong passion for your work.

Required Qualifications

• Master’s degree in a quantitative field (Operations Research, Computer Science, Engineering, Applied Math, Statistics, Physics, Analytics, etc.) or equivalent work experience.
• Proven leadership in applying and scaling analytics and machine learning techniques to extract significant insights from data.
• Proficiency in scientific computing methods using tools such as Python, R, or Scala.

Preferred Qualifications

• Experience applying analytic methodologies such as Machine Learning, Optimization, and Simulation to real-world problems.
• Experience working with large datasets and cloud computing environments.
• Familiarity with DevOps environments and tools, including Git and CI/CD workflows.
• A continuous learner who stays updated with the latest technology trends and actively shares knowledge with peers.

Benefits & Perks

• Compensation: Varies based on factors such as office location, role, qualifications, skill set, and experience.
• Total Rewards: Includes salary, bonus (if applicable), and benefits. Additional details will be provided during the hiring process.