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Pipeline Implementation: Implement and maintain machine learning and use case pipelines alongside experienced data scientists and big data engineers.

Hypothesis Testing & Analytics: Test business hypotheses from raw data sets, draw meaningful conclusions, and execute deep statistical modeling across various domains.

Stakeholder Communication: Communicate complex analytical results and algorithmic models verbally, in writing, and through effective visualizations to product managers, customers, and senior management.

Cross-Functional Collaboration: Work dynamically with cross-functional business stakeholders to successfully translate commercial issues into viable, scalable analytics solutions.

Academic Standing: Must hold a Bachelor’s degree (or equivalent) specifically in quantitative fields such as Computer Science or Engineering.

Experience Level: Open exclusively to fresh graduates up to a maximum of 2 years of professional data or tech experience.

AI & ML Competency: Must be highly competent in machine learning principles, mathematics, statistics, deep learning, and cutting-edge generative AI techniques.

Programming & Big Data: Proficient in implementing data transformations and algorithms using statistical packages and ML libraries (Python, Sklearn, PyTorch, Keras, SciPy, NLTK, Spark MLlib). Familiarity with Big Data technology (Hadoop, interactive SQL on Hadoop, Spark) is required.

Data Visualization: Familiar with utilizing leading enterprise visualization tools, specifically Tableau or PowerBI, to present data insights.

Demand Forecasting: Forecast highly complex customer demand models to ensure thousands of different products hit retail shelves in precise quantities and exact timeframes.

Information Flow Management: Handle the critical, high-volume daily information flows encompassing corporate orders, international shipments, and vendor invoices.

Physical Distribution Leadership: Lead the end-to-end physical distribution process, seamlessly moving inventory from global Distribution Centres directly to the customer’s shelf.

Digital Supply Chain Integration: Develop sophisticated, integrated logistics approaches by leveraging the latest advancements in digitized manufacturing plants and connected smart technology.

Sustainable Operations: Work autonomously to execute high-impact logistical projects that enhance the overall efficiency and sustainability of P&G’s Supply Network Operations (SNO).

Graduation Cohort: Must be actively pursuing a Bachelor’s degree with an official graduation date of either December 2026 or June 2027.

Targeted Majors: Exclusively open to students studying Engineering (all disciplines), Actuarial Sciences, Computer/Data Science, Mathematics (Statistics), Tech Management, or Supply Chain/Logistics.

Technical Stack: Demonstrate strong operational proficiency in Microsoft Office, paired with highly preferred foundational knowledge of Programming and Algorithms.

Leadership & Analytics: Exhibit born leadership capabilities through academic or non-academic achievements, alongside exceptionally strong analytical and problem-solving skills.

Linguistic & Soft Skills: Exhibit high English proficiency and the agile ability to collaborate effectively with diverse, cross-functional global teams.