AWS Monetization Data Science Manager, Data Science Manager - AWS Billing Data Analytics and Insights

Key Skills

Java Programming, Python Programming, SQL, Big Data Technology, Machine learning techniques, Pandas, R Programming, Amazon RedShift, Amazon Elastic Compute Cloud-EC2, Amazon RDS, SPARK Programming, AWS Sagemaker, DynamoDB, Lambda, Amazon Simple Storage Service (S3), Data pipelines, ETL frameworks

Job Description

Are you interested in building the next generation, cloud-based commerce system for AWS that’s used by millions of customers worldwide? Are you excited by the idea of building real-time stream processing systems that operate at Petabyte scale? Do you want to make an impact at a $10-billion-a-year business? Then we need to talk!

About the hiring group

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.

Job responsibilities

The successful candidate will be an analytical problem solver who enjoys diving into data, is excited about solving ambiguity problems, can multi-task, and can credibly interface between technical teams and business stakeholders.

Inclusive Team Culture

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 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 professional and enable them to take on more complex tasks in the future.

BASIC QUALIFICATIONS

• Master’s degree in Mathematics, Statistics, Computer Science or in another related field.
• 2+ years of hands-on relevant, technical industry experience.
• Deep understanding of Statistical Analysis, Modeling and Machine Learning techniques.
• Experience in designing and deploying ML modeling and prediction pipelines.
• Ability to leverage SQL or Spark for Ad-hoc analyses and building out ETL pipelines on heterogeneous data sources.
• Experience using programming/scripting languages such as Python or equivalent.
• Experience performing statistical analysis and using tools such as R, pandas, or equivalent.
• Familiarity with AWS Redshift, Spark or other distributed computing technologies.
• Excellent written and verbal communication skills.
• Ability to dive deep into complex technical problems and drive change.
• Excellent problem solving skills with a strong attention to detail.
• Ability to work in a fast-paced, ambiguous environment while prioritizing and managing multiple responsibilities.

PREFERRED QUALIFICATIONS

• Experience and proficiency with AWS technologies (EC2, CloudTrail, S3, SageMaker, Lambda, DynamoDB, RDS, etc.), and Big Data technologies.
• Demonstrated skill and passion for operational excellence.