- 2+ years of data scientist experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Bachelor's degree
- 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.
As a Data Scientist on the Amazon Business Risk and Abuse Management team, you will be at the forefront of developing sophisticated machine learning models to protect the integrity of Amazon's B2B space. Your primary focus will be on designing and implementing advanced detection systems that analyze customer behavior at registration and throughout their journey. You'll leverage diverse data signals including customer profiles, purchase patterns, and network associations to identify potential abuse and fraudulent activities. Working with state-of-the-art machine learning techniques and AWS services, you'll build robust models that can effectively distinguish between legitimate business activities and suspicious behavior patterns.
A crucial aspect of your role will be developing intelligent growth-enabling systems that balance risk and opportunity. You'll create advanced classification models to accurately segment customers into reseller and non-reseller categories, while simultaneously building sophisticated customer profiling models. These models will be instrumental in determining optimal purchasing limits that minimize potential abuse while maximizing business growth and profitability. You'll work closely with cross-functional teams to understand complex business requirements, conduct thorough data analysis, and implement scalable solutions using serverless architectures and AWS services. The ideal candidate will possess strong analytical and problem-solving skills, expertise in machine learning and statistical modeling, and the ability to translate complex technical concepts into actionable business insights.
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
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