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GroupSolver at GroupSolver, Inc.

Remote: 
Full Remote
Contract: 
Experience: 
Mid-level (2-5 years)
Work from: 
California (USA), Texas (USA)

Offer summary

Qualifications:

MS/PhD in relevant field, 2+ years of experience in predictive modeling or ML.

Key responsabilities:

  • Develop NLP models for market research
  • Work with international teams to improve research practices

Job description

GroupSolver is a market research tech startup based in San Diego with offices in Utah and Kosice, Slovak Republic. Combining AI and Crowd Intelligence, our technology helps decision makers and researchers find insights, which would otherwise remain hidden from traditional online surveys. Our clients include leading companies such as Google, Adidas, General Mills, Discovery, Lenovo, and Amazon.

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  • Research and development: work with and develop state-of-the-art NLP models to improve conventional market research practices.

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Basic Qualifications:

  • MS/PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, or a related field.
  • 2+ years of hands-on experience in predictive modeling, ML or large data analysis
  • Algorithm and model development experience for large-scale applications
  • Proficiency in at least one of the following languages: Python, R/Matlab, Java
  • Comfortable working with teams in different time zones, (USA, Europe)
  • Good communication skills, ability to explain technical concepts to non-technical audiences.

Preferred Qualifications:

  • Strong understanding of Transformer architecture and Attention mechanisms.
  • 2 years of experience in NLP
  • Familiarity with spaCy, AllenNLP, Gensim, Pytorch, Tensorflow, Deep Learning
  • Knows the difference between RNN, CNN, LSTM, GANs.
  • Familiar with Meta AI, Deepmind, Google AI, OpenAI and other big players.

Required profile

Experience

Level of experience: Mid-level (2-5 years)
Spoken language(s):
Check out the description to know which languages are mandatory.

Other Skills

  • Verbal Communication Skills
  • Teamwork

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