10 дней назад
Data Science Intern (Semester 2026) - P&G Management Internship Program - Bachelor's Degree or above (Data Science)
Мэтч & Сопровод
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Описание вакансии
Текст:
TL;DR
Data Science Intern (Data Science): Building and deploying machine learning and data science models for supply chain, retail, media, eCommerce, and consumer analytics with an accent on Python, statistical modeling, and business insights. Focus on investigating datasets from more than 10 countries, validating models, and solving complex business problems across cross-functional teams.
Location: Singapore General Office
Company
Procter & Gamble produces globally recognized consumer brands and operates in approximately 70 countries.
What you will do
- Join a central or embedded data science team focused on supply chain, retail, media, eCommerce, and consumer analytics.
- Investigate point-of-sale, geospatial, product and supply, direct-to-consumer, CRM, TV media, and online search datasets.
- Generate actionable insights from data covering more than 10 countries across the region.
- Build, validate, test, and deploy machine learning and other data science models into IT platforms.
- Collaborate with cross-functional teams and translate business objectives into analytical solutions.
Requirements
- Penultimate- or final-year student able to commit to a full-time six-month internship.
- Bachelor’s degree or above in Computer Science, Mathematics, Economics, Statistics, Applied Science, or another quantitative field.
- Proficiency in Python.
- Experience with machine learning, statistical modeling, or econometrics through coursework or internships.
- Familiarity with operations research, including optimization and simulation, and machine learning models such as tree models, deep learning, or reinforcement learning.
- Strong communication, problem-solving, prioritization, and cross-functional collaboration skills.
Nice to have
- Knowledge of big data environments and Spark.
Culture & Benefits
- Hands-on experience with industry-leading analytical tools and technologies from the first day.
- Formal training and day-to-day mentoring from IT and data science professionals.
- Collaboration with passionate cross-functional teams.
- Work on real-life projects with responsibilities from the first day.
- Inclusive culture focused on equal employment opportunities and diverse perspectives.
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