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Amazon Applied Scientist India, Karnataka, Bengaluru 21871923
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Key job responsibilities
• Understand the business and discover actionable insights from large volumes of data through application of machine learning, statistics or causal inference.
• Analyse and extract relevant information from large amounts of Amazon’s historical transactions data to help automate and optimize key processes
• Research, develop and implement novel machine learning and statistical approaches for anomaly, theft, fraud, abusive and wasteful transactions detection.
• Use machine learning and analytical techniques to create scalable solutions for business problems.
• Identify new areas where machine learning can be applied for solving business problems.
• Partner with developers and business teams to put your models in production.
• Mentor other scientists and engineers in the use of ML techniques.
A day in the life
• Understand the business and discover actionable insights from large volumes of data through application of machine learning, statistics or causal inference.
• Analyse and extract relevant information from large amounts of Amazon’s historical transactions data to help automate and optimize key processes
• Research, develop and implement novel machine learning and statistical approaches for anomaly, theft, fraud, abusive and wasteful transactions detection.
• Use machine learning and analytical techniques to create scalable solutions for business problems.
• Identify new areas where machine learning can be applied for solving business problems.
• Partner with developers and business teams to put your models in production.
• Mentor other scientists and engineers in the use of ML techniques.Bangalore, KA, IND
BASIC QUALIFICATIONS
- PhD, or Master's degree and 5+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
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