Data Scientist

Key Skills

C# Programming, C++, Java Programming, Perl Programming, Python Programming, Scala Programming, SQL

Job Description

Job summary

The AWS Applications team builds powerful, intuitive, and market-defining business and productivity applications to help our customers stay ahead of their changing business needs, and remove the burden of undifferentiated heavy lifting that business users go through daily. We are building a new category of AWS applications that will make customer-centric technology developed to support Amazon.com available to AWS customers. These applications will leverage the power of machine learning and the large ecosystem of AWS services such as SageMaker, AWS Lambda, Amazon S3, Kinesis, Glue, and Amazon QuickSight to provide a truly frustration-free, easy-to-use, extensible, and natural customer experience. This is a green-field chance to build a unique set of services that combines ML, big data, and serverless technologies from scratch.

Joining the AWS Apps team gives you the opportunity to:

• Solve challenging problems and help customers modernize their core IT applications
• Work for a company that’s a recognized leader in the cloud computing space
• Have direct impact on hundreds of thousands of users of AWS Apps services
• Lead customers on their transformation journey to big data and machine learning

The successful candidate is a curious and analytical problem solver who enjoys diving into data, is excited about investigations and algorithms, can multi-task, and can credibly interface between technical teams and business stakeholders. Your analytical abilities, business understanding, and technical savvy will be used to identify specific and actionable opportunities to solve existing business problems and look around corners for future opportunities.

This role can be located in Seattle, WA, Austin, TX, or Atlanta, GA.

Key job responsibilities

As a Data Scientist, you will discover and solve real world problems by analyzing large amounts of business data, defining new metrics and business cases, designing simulations and experiments, creating models, and collaborating with colleagues in business, software, and research. You will get the exciting opportunity to work on some of the world’s largest and diverse datasets. You will work closely with scientists and engineers to develop and run statistical models and produce modeling solutions. You will partner with engineers to build end-to-end data pipelines and production code, and have exposure to senior leadership as we communicate results and provide scientific guidance to the business. You will use Amazon’s wealth of data to help answer tough questions with the full AWS stack at your disposal, analyzing large amounts of data, automating and scaling the analysis, and developing metrics that will guide our direction and enable us to continually delight Amazonians worldwide.

BASIC QUALIFICATIONS

• Master’s degree or foreign equivalent in Statistics, Computer Science, Applied Math, Operations Research, Economics, Business Analytics or a related field.
• 4+ years of experience applying various machine learning techniques, and understanding the key parameters that affect their performance.
• 2+ years of experience with data querying languages (e.g. SQL), scripting languages (e.g. Python, Perl, Scala, Java, C#, C++, etc).
• Have a history of building systems that capture and utilize large data sets in order to quantify performance via metrics or KPIs.
• Experienced in using multiple data science methodologies to solve complex business problems
• Experience in standard machine-learning and statistical modeling tools and techniques (e.g. random forests, gradient-boosted regression, LASSO, logistic regression, etc)
• Understands the data science life cycle and capable of contributing to all aspects of the cycle, in collaboration with engineering teams.
• Strong troubleshooting and problem solving skills.
• Thrive in a fast-paced, innovative environment.

PREFERRED QUALIFICATIONS

• Ph.D. degree or foreign equivalent in Statistics, Computer Science, Applied Math, Operations Research, Economics, Business Analytics or a related field.
• Experience processing, filtering, and presenting large quantities (Millions to Billions of rows) of data
• Experience in advanced machine-learning and statistical modeling tools and techniques (e.g. Graph Neural Networks, Transformers, Auto-encoders, Time Sequence Modeling etc)
• Capable of researching and experimenting state of the art ML solutions from academic and industry research and applying them to solve business problems.
• Experienced in AWS toolkits including SageMaker, S3, Lambda, Step Functions etc.
• Experience building complex data visualization
• Sound business judgment with demonstrated ability to balance technical and business needs to make the right decisions about technology, models and methodologies.
• Demonstrated ability to independently drive issues to resolution while communicating insights to non-technical audiences.
• Excellent written and verbal communication skills with the ability to convey mathematical results to non-science stakeholders
• Experience in developing and running production level software including CI/CD, ML model deployment, containers, or/and MLOps.