Sr. Data Scientist, AWS Training and Certification

Job summary
As cloud technologies continue to transform businesses, skilled individuals are in high demand. At AWS Training and Certification (T&C), we are passionate about revolutionizing the way people advance their cloud skills and careers. We equip diverse builders of today and tomorrow with the knowledge they need to leverage the power of the AWS Cloud. Join our dynamic, fast-growing team and help us empower our customers to build cloud skills.

We are seeking a Sr. Data Scientist to join our new Data Science function in the AWS Training organization. This team owns the design and implementation of scalable and reliable approaches to support or automate decision making throughout the business.

You will do this by analyzing data with a variety of statistical techniques and then building, validating, and implementing models based your analysis. You will not be able to do this alone. You will need to build partnerships across data, engineering, and business teams. This is a hands-on role which requires someone that is motivated to roll up their sleeves and become a builder themselves when needed. Software and Data Engineering skills will give you an edge. If you are successful, you will see your analysis inform not only business decision making, but your models will become part of our core training products such as AWS Skill Builder (https://skillbuilder.aws).

About Us
As cloud technologies continue to transform businesses, skilled individuals are in high demand. At AWS Training and Certification (T&C), we are passionate about revolutionizing the way people advance their cloud skills and careers. We equip diverse builders of today and tomorrow with the knowledge they need to leverage the power of the AWS Cloud. Join our dynamic, fast-growing team and help us empower our customers to build cloud skills.

Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have twelve 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 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

Work/Life Balance
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. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded employee and enable them to take on more complex tasks in the future.

Key job responsibilities
* Proactively seek to identify business opportunities and insights and provide solutions to automate and optimize key business processes and policies based on a broad and deep knowledge of Amazon and AWS data, industry best-practices, and work done by other teams.
* Apply a range of data science techniques and tools combined with subject matter expertise to solve difficult customer or business problems and cases in which the solution approach is unclear.
* Dive deep into the broader AWS business as well as the our T&C data to identify opportunities to leverage this data for building these solutions.
* Acquire this data by accessing data sources and building the necessary SQL/ETL queries or scripts.
* Import processes through various company specific interfaces for accessing data storage systems including Salesforce, S3, Redshift, and others.
* Audit data and other models across the business to identify defects or inefficiencies which materially impact the customer or business, but can be mitigated through corrective actions.
* Analyze data for trends and input validity by inspecting univariate distributions, exploring bivariate relationships, constructing appropriate transformations, and tracking down the source and meaning of anomalies.
* Build models and automated tools using statistical modeling, mathematical modeling, econometric modeling, network modeling, social network modeling, natural language processing, machine learning algorithms, genetic algorithms, and neural networks.
* Validate these models against alternative approaches, expected and observed outcome, and other business defined key performance indicators.
* Implement these models in a manner which complies with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production.
* Enable product engineering teams to consume your models through services which can directly power customer-facing experiences.
* Inspect the key business metrics/KPIs (even if you did not create them) when your analytics work points to potential gaps or opportunities; providing clear, compelling analyses by leveraging your knowledge across AWS and Amazon data to support the broader business.
* Initiate machine learning projects to address long-term business needs and predicting key metrics to support business decision making.

About the team
The AWS Training organization anticipates learner needs to deliver accessible, respected learning experiences that inspire and empower learners at all levels to build with confidence on the AWS Cloud. We are a global team of builders who are passionate about the opportunity to have a positive impact on people's lives through the delivery of compelling learning experiences.

This position can be remote, but candidates must be based near an AWS office location (Atlanta, Austin, Boston, Chicago, Cupertino, Dallas, Denver, Detroit, East Palo Alto, Herndon, New York City, Pittsburgh, Portland, San Francisco, Santa Monica, Seattle, Irvine, or Tempe)

Basic Qualifications

* Master's Degree with 5+ years experience in Machine Learning, AI, Decision Science, Operations Research, Industrial and Systems Engineering, Statistics, Applied Mathematics, Computer Science, Business Analytics, Data Science, Economics, or a related field
* 3+ years of experience of building predictive models for business and proficiency in model development and model validation.
* 2+ years of experience in a stakeholder or customer-facing analyst or scientist role.
* Experience with programing skills in Python, R, SQL or Scala.
* Experience with AWS technologies like Redshift, S3, Sagemaker, EC2, Data Pipeline, & EMR.
* Experience with time series modeling and machine learning forecasting.

Preferred Qualifications

* PhD degree in Machine Learning, AI, Decision Science, Operations Research, Industrial and Systems Engineering, Statistics, Applied Mathematics, Computer Science, Business Analytics, Data Science, Economics, or a related field
* 5+ years of experience working in data science in a consumer product company
* Evidence of completed science work with high positive impact on business outcomes.
* Proven achievements of developing and managing a long-term research vision and portfolio of research initiatives, that have been successfully integrated in production systems or informed policy decisions.

The pay range for this position in Colorado is $159,000 - $215,000[yr]; however, base pay offered may vary depending on job-related knowledge, skills, and experience. A sign-on bonus and restricted stock units may be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits, dependent on the position offered. This information is provided per the Colorado Equal Pay Act. Base pay information is based on market location. Applicants should apply via Amazon’s internal or external careers site.

Pursuant to the San Francisco and Los Angeles Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Pursuant to the Los Angeles Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.



Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.