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KDnuggets Home » Jobs » P&G: Data Scientist – Machine Learning/NLP [Cincinnati, OH] ( 18:n47 )

P&G: Data Scientist – Machine Learning/NLP [Cincinnati, OH]


P&G is seeking a Data Scientist - Machine Learning/NLP in Cincinnati, OH. In this role you will have multiple projects on which you will leverage machine learning tools to solve these types of problems.



At: P&GP&G
Location: Cincinnati, OH
Web: www.pg.com
Position: Data Scientist - Machine Learning/NLP

Apply here.

At P&G we leverage advanced machine learning methods to solve challenging Research and Development problems. These challenges range from developing smart products, personalizing consumer experiences and understanding our consumers in depth. In this role you will have multiple projects on which you will leverage machine learning tools to solve these types of problems. You will be part of a diverse, global team with similar backgrounds and projects with which you can collaborate to help find solutions.

We are looking for a Data Scientist to join our Data Science & AI team in the area of speech and Natural Language Processing (NLP). Are you up to the challenge to transform the way we innovate at P&G?

What You Will Do:

  • Translate business challenges into clear machine learning problem statements
  • Do research on emerging machine learning and deep learning solutions applied to natural language and unstructured data.
  • Develop scalable deep learning and NLP solutions through prototyping and proof-of-concept
  • Work with Data Engineers and DevOps to deploy machine learning applications to solve business problems

What We're Looking For:

  • PhD in Computer Science, Computer Engineering or a closely related field
  • Extensive experience with wide range of advanced machine learning methods (such as NLP, Deep (Reinforcement) Learning, Bayesian and Monte Carlo Methods, Probabilistic Graphical Models. Dynamic Programming & Optimal Control Theory)
  • In depth understanding of Deep Learning and experience with NLP methods for information extraction, topic modeling, parsing, and relationship extraction
  • Ability to explain your work clearly to non-experts
  • Strong software engineering skills and the ability to build systems at scale
  • Experience building machine learning systems by applying best-in-class solutions including feature engineering, and tuning of model hyper-parameters
  • Experience in building large-scale NLP systems from researching a prototype to production

What We Offer:

  • Competitive remuneration
  • Retirement Plan
  • Health Care Benefits
  • Paid time off
  • Health and Wellness Programs

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