Data Scientist , ABDAI

- 2+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 2+ years of data scientist experience
- 2+ 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
- Experience in Python, Perl, or another scripting language
- Experience in a ML or data scientist role with a large technology company

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.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $125,500/year in our lowest geographic market up to $212,800/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
Come be a part of a rapidly expanding $35 billion-dollar global business. At Amazon Business, a fast-growing startup passionate about building solutions, we set out every day to innovate and disrupt the status quo. We stand at the intersection of tech & retail in the B2B space developing innovative purchasing and procurement solutions to help businesses and organizations thrive. At Amazon Business, we strive to be the most recognized and preferred strategic partner for smart business buying. Bring your insight, imagination and a healthy disregard for the impossible. Join us in building and celebrating the value of Amazon Business to buyers and sellers of all sizes and industries. Unlock your career potential.

Amazon Business Data Insights and Analytics team is looking for a Data Scientist to lead the research and thought leadership to drive our data and insights strategy for Amazon Business. This role is central in shaping the definition and execution of the long-term strategy for Amazon Business.

You will be responsible for researching, experimenting and analyzing predictive and optimization models. You will work on ambiguous and complex business and research science problems with large opportunities. You are an analytical individual who is comfortable working with cross-functional teams and systems. You must be a self-starter and be able to learn on the go. Excellent written and verbal communication skills are required as you will work very closely with diverse teams.

Key job responsibilities
- Interact with business and software teams to understand their business requirements and operational processes
- Frame business problems into scalable solutions
- Adapt existing and invent new techniques for solutions
- Gather data required for analysis and model building
- Create and track accuracy and performance metrics
- Prototype models by using high-level modeling languages such as R or in software languages such as Python.
- Familiarity with transforming prototypes to production is preferred.
- Create, enhance, and maintain technical documentation