Data Science Intern

We are a boot-strapped startup headquartered in California and have a research center in Rochester hills. We are primarily into Artificial Intelligence, helping manufacturing companies with Quality inspections using our software and external camera. We are now a 5-year young company, our vision is to be unique in what we do and become an inspiration for the whole industry.

We are looking for motivated data scientists with the ability to develop, automate, and run analytical models of our systems. Academic and/or practical background in ComputerScience, Engineering, Operations Research, or Process Control is particularly relevantfor this position. Experience in the integration of model-based engineering tools and/ormultidisciplinary analysis & optimization is also a plus.

Or you could simply be crazy about doing something great with computer vision and AI and want to change the world. You have all it takes to be the next computer vision wizard. Then let's chat at our OU Inc office, which is not too far from your OU campus.

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 novelapproaches related to forecasting and prediction. Identify, develop, manage, and executeanalyses to uncover areas of opportunity and present written business recommendations
• Collaborate with remote teams working on different time zones, 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.
• Excellent communication and data presentation skills.
• Preferred Qualifications: Graduates, Masters or equivalent advanced degree in ComputerScience, Computer Engineering, Statistics, Mathematics, or related technical discipline.Hands-on experience and project-based learning in computer science, engineering ormathematics 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 AmazonEMR, AWS Lambda, SageMaker, Machine Learning, IoT, Amazon DynamoDB, Amazon S3, andAmazon EC2 Container Service.