Amazon Data Scientist AWS Networking - SIGNAL 

Australia, New South Wales, Sydney 

498509173

Networking Analytics is looking for an experienced Data Scientist to be a part of a team solving complex data processing problems generating latency insights (building using big data, ML and potentially AI). This is a blue-sky role that gives you a chance to roll up your sleeves and dive into big data sets in order to build simulations and experimentation systems at scale, build optimization algorithms across Amazon. This is an opportunity to think big about how to solve a challenging problem for our customers and understand their requirements for products.
Key job responsibilities
A day in the life- Propose Data Science solutions, create prototypes and simulations to test them
- Work closely with data engineers and software development engineers to integrate prototypes into production systems
- Utilize code (SQL/Python/R) for data analyzes and modeling algorithms (including tensorflow, etc, open source packages)
- Contribute to process improvements, data infrastructure/pipeline developmentAbout the team
About AWS
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.Work/Life Balance

- 2+ years of data scientist experience
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Experience applying theoretical models in an applied environment