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Applied R&D
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GS Global Services
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1900000I8C Requisition #
Thanks for your interest in the ML Engineer position. Unfortunately this position has been closed but you can search our 6 open jobs by clicking here.
Requirements:  
  • Deep understanding of statistical and predictive modeling concepts, machine-learning approaches, clustering and classification techniques, recommendations and optimization algorithms.
  • Experience in delivering world-class data science outcomes, solving complex analytical problems using quantitative approaches with unique blend of analytical, mathematical and technical skills.
  • Passion about asking and answering questions in large datasets, and ability to communicate that passion to product managers and engineers.
  • Very good applied statistics and mathematics skills
  • Data oriented personality
  • Great communication skills
  • Comfortable in working in international teams, virtual and cross-functional
  • Certifying MOOCS (Coursera, Stanford, etc...) can be a complement
  • Solid knowledge in statistics: descriptive analysis (Student's test, Fisher test, ANOVA, Chi2, etc…), supervised and unsupervised analysis (regressions, CAH, PCAn, K-Means, decision trees, etc...)
  • Machine Learning: linear and logistic regressions, discriminant analysis, bagging, boosting, random forests, gradient boosting, neural networks, text mining and topics extraction, etc.
  • Deep Knowledge and experience with common data science toolkits and scripting languages: R , Python (sklearn, panda, numpy,..) or Spark (Mlib) data science libraries
  • Experience with common data science toolkits and scripting languages
  • Ability to investigate issues and come up with resolutions for large data sets a must
  • Ability to work independently and be a self-starter
  • Excellent organizational and communication skills
  • Fluent in English (written and verbal).
     

Nice to have: 

  • Agile best practices experienced
  • Cloud basic concepts understanding
 
Education:
  • Bachelor’s degree minimum, Master and PhD Degree considered in priority – Mathematics, Statistic, Machine Learning, Data Science, Computer Science, Physics
  • 5+ years of experience applying statistical concepts and methods, including predictive techniques from data source.

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