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Co-op / Intern - Data Science
P&G is the largest consumer packaged goods company in the world. We have operations in over 75 countries, with 65 trusted brands that improve lives for 5 billion consumers worldwide. This brings many advantages, including the opportunity for our employees to enjoy a diverse and rewarding lifelong career filled with new and exciting challenges.
Are you looking for a position that offers a rewarding lifelong career filled with new and exciting challenges? P&G is looking for an Co-op / Intern - Data Science.
Co-op / Intern - Data Science
In this role, you will leverage data analytics and advanced machine learning methods including deep learning (DL) to solve important, company-wide R&D challenges. The work scope includes exploring internal and external data sources, developing predictive models with cutting edge technologies, implementing model deployment and demonstrating efficiency and business impact. As a data science expert, you will collaborate with scientists and engineers to experiment and deliver solutions and tools which will improve the lives of our consumers. You will also partner with product researcher and designers to understand the consumer need and technical challenges, brainstorm technical solutions, guide and influence technical project direction by leveraging your data science background. You will feel the ownership of your project from the beginning and receive mentoring from your manager. This co-op / intern position is full time based on a 40-hour work week, working on site is preferred. The Fall Co-op session is approximately September through December, the Spring Co-op session is approximately January through May.
Must be currently enrolled in a degree program in computer science, or data science, bioinformatics, statistics, engineering, etc., a Master program is beneficial. Fundamental knowledge of and experience with machine learning methods including deep learning (DL) is required. Experience of using python and machine learning packages such as NumPy, Pandas, scikit-learn, Tensorflow, PyTorch, etc. Experience with developing, fine-tuning, optimizing machine learning models or predictive models is preferred. Experience with deep learning applications including computer vision, natural language processing (NLP), graph representation learning, time series or other method application is a plus.
Just So You Know:
Pay Range: $29-$50 /hr
Compensation for roles at P&G varies depending on a wide array of non-discriminatory factors including but not limited to the specific office location, role, degree/credentials, relevant skill set, and level of relevant experience. At P&G compensation decisions are dependent on the facts and circumstances of each case. Total Rewards at P&G include salary + bonus (if applicable) + benefits. Your recruiter may be able to share more about our total rewards offerings and the specific salary range for the relevant location(s) during the hiring process.
We are committed to providing equal opportunities in employment. We value diversity and do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Immigration sponsorship is not available for this position, except in rare situations based on Procter & Gamble's sole discretion. Applicants for U.S. based positions are eligible to work in the U.S. without the need for current or future sponsorship. We do not sponsor for permanent residency. Any exceptions are based on the Company's specific business needs at the time and place of recruitment as well as the particular qualifications of the individual.
Procter & Gamble participates in e-verify as required by law.
Qualified individuals will not be disadvantaged based on being unemployed.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
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