Microsoft Data & Applied Scientist II 

India, Telangana, Hyderabad 

78972000

Required Qualifications:

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research)
  • OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
  • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
  • OR equivalent experience.

Additional or Preferred Qualifications:

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research)
  • OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
  • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
• 3+years of professional experience applying Deep learning, Machine Learning concepts in real world applications.
• Research and/or development experience with machine learning, NLP and data mining.
• Experience in architecting, developing, and delivering advanced NLP projects.

• Developing novel machine learning and data mining algorithms.
• Designing and developing solutions that respond in real time.
• Build data quality checks and re-usable modules for the training.
• Host ML models with production-ready code.
• Designing and executing offline/online experiments.
• Advancing the state of the art of NLP technologies for real world scenarios.
• Investigating and solving NLP accuracy and robustness issues across all processing chains, including model development, test and quality control, deployment, and user feedback stages.