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Procter & Gamble · 2 days ago

Data Scientist

Cincinnati, OH

Full-time

Onsite

New Grad, Entry Level

$85K/yr - $115K/yr

Procter & Gamble is seeking a Data Scientist to solve complex data science problems and implement innovative models that enhance business processes. The role involves designing algorithms, collaborating with engineering teams, and mentoring others while utilizing advanced techniques in Artificial Intelligence and machine learning.

BeautyBrand MarketingCleaning ProductsConsumer GoodsCosmeticsNutritionPersonal Health

Growth Opportunities

No H1B

Responsibilities

Algorithm Design & Development: Directly contribute to the design and development of scalable Data Science algorithms

Collaboration: Work closely with Data and Software Engineering teams to effectively productionize algorithms

Data Analysis: Apply thorough technical knowledge to large datasets, conducting exploratory data analysis, feature engineering, and model building

Coaching & Mentorship: Develop others as a technical coach, sharing your expertise and insights

Expertise Development: Become a known expert in one or multiple Data Science techniques and methodologies

Qualification

PythonMachine LearningOperations ResearchCloud ComputingData AnalysisGenerative AIDevOps FamiliarityCommunicationContinuous Learning

Required

Education: Pursuing or has graduated with a Master's degree in a quantitative field (Operations Research, Computer Science, Engineering, Applied Mathematics, Statistics, Physics, Analytics, etc.) or possess equivalent work experience

Technical Skills: Proficient in programming languages such as Python and familiar with data science/machine learning libraries like OpenCV, scikit-learn, PyTorch, TensorFlow/Keras, and Pandas. Demonstrated ability to develop and test code within cloud environments

Communication: Strong written and verbal communication skills, with the ability to influence others to take action

Preferred

Analytic Methodologies: Experience applying analytic methodologies such as Machine Learning, Optimization, Simulation, and Generative and Agentic AI to real-world problems

Continuous Learning: A commitment to lifelong learning, keeping up to date with the latest technology trends, and a willingness to teach others while learning new techniques

Data Handling & Cloud: Experience with large datasets and developing in cloud computing platforms such as GCP or Azure

DevOps Familiarity: Familiarity with DevOps environments, including tools like Git and CI/CD practices