Data Scientist Intern

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

Amazon's looking for Data Scientist to optimize one of the most complex logistics systems in the world. Academic and/or practical background in Computer Science, Engineering, Operations Research, or Process Control are particularly relevant for this position. Experience in the integration of model-based engineering tools and/or multidisciplinary analysis & optimization is also a plus.
Major Responsibilities:
· Use data analyses and statistical techniques to develop solutions to improve customer experience and to guide business decision making
· Identify predictors and causes of business related problems and implement novel approaches related to forecasting and prediction
· Identify, develop, manage, and execute analyses to uncover areas of opportunity and present written business recommendations
· Collaborate with multiple teams as a leader of quantitative analysis and where you develop solutions that utilize the highest standards of analytical rigor and data integrity
· Analyze and solve business problems at their root

BASIC QUALIFICATIONS

• Pursuing Masters or equivalent advanced degree from a top tier Technology school
• Record of delivering large analytical solutions with business impact
• Experience on R/SAS/Matlab and SQL
• Excellent Microsoft Office skills, including a strong working knowledge of Excel
• Problem solving ability and passion for big data
• Excellent communication and data presentation skills
• Fluent written and spoken English

PREFERRED QUALIFICATIONS

Masters or equivalent advanced degree in Computer Science, Computer Engineering, Statistics, Mathematics or related technical discipline. Hands-on experience and project based learning in computer science, engineering or mathematics is preferred.
• Academic experience in manipulating/transforming data, model selection, model training, cross-validation and deployment at scale.
• Academic or Project Experience with Machine and Deep Learning toolkits such as MXNet, TensorFlow, Caffe and PyTorch.
• Academic Experience with Big Data platforms like Apache Spark and Hadoop.
• Familiarity with data processing with Python, R & SQL.
• Familiarity with AWS services related to AI/ML highly desirable, particularly Amazon EMR, AWS Lambda, SageMaker, Machine Learning, IoT, Amazon DynamoDB, Amazon S3, Amazon EC2 Container Service, Green Grass etc.