Amazon is looking for an outstanding Data Scientist to join the AWS Product Analytics team. This is your opportunity to be a core part of the team that has direct impact on affecting the long term roadmap of the AWS EC2 Product Team. This role is within a larger Data science, Business Intelligence & Data engineering team that focuses on broad data exploration, quantitative methodology, and statistical modeling to drive actionable data intelligence in AWS.
Since early 2006, AWS has provided companies of all sizes with an infrastructure platform in the cloud. AWS is a high-growth, fast-moving division within Amazon with a start-up mentality where new and diverse challenges arise every day. On the AWS Product Analytics team you will be surrounded by people that are exceptionally talented, bright, and driven, and believe that world class Data Science is critical to our success. To help build this growing team, you must be highly analytical and possess a strong passion for analytics and accountability, set high standards with a focus on superior business success. We take working hard, having fun, and making history seriously. AWS sets the standard for functionality, cost, and performance for many cloud based services, but it’s still early days for cloud computing, and there are boundless opportunities to continue to redefine the world of cloud computing - come help us make history!
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. The successful candidate will have a strong quantitative background and can thrive in an environment that leverages statistics, machine learning, operations research, econometrics, and business analysis.
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.
Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
· Master’s degree or foreign equivalent in Statistics, Applied Math, Operations Research, Economics,Business Analytics, MIS, or a related field and one year of experience in the job offered or in a related occupation. Employer will accept a Bachelor’s degree or foreign equivalent in Statistics, Applied Math, Operations Research, Economics,Business Analytics, MIS, or a related field and five years of experience in the job offered or a related field as equivalent to the Master’s degree and one year of experience.
· 1+ years of experience applying various machine learning techniques, and understanding the key parameters that affect their performance.
· 1+ years' of experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), and statistical/mathematical software (e.g. R, SAS, Matlab, etc.)
· Have a history of building systems that capture and utilize large data sets in order to quantify performance via metrics or KPIs.
· Understanding of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.
· 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)
· Experience in using dimensionality reduction techniques on large datasets
· Experienced in handling large data sets using SQL and databases in a business environment.
· Excellent verbal and written communication.
· Strong troubleshooting and problem solving skills.
· Thrive in a fast-paced, innovative environment.
· Experience processing, filtering, and presenting large quantities (Millions to Billions of rows) of data
· Demonstrated grasp of the fundamental concepts and mathematics of machine learning and deep learning.
· 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.
Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation