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.
The Analytics Data Product & Tech (ADAPTech) team is a strategic partner to the WW Sales organization, playing a key role in driving sales productivity through three primary workstreams. First, the Analytics team provides data-driven insights and reporting tools to measure business, customer, and employee performance. Second, the Products and Science team develops transformative tools that help Account Executives (AEs) to prioritize accounts, recommend product features, and engage more effectively with customers. Finally, the Data Management and Governance teams ensure AEs have access to accurate and enriched customer information across our tools. We're seeking an Data Scientist to join our team to improve the productivity and efficiency of AEs. You'll be part of expanding GenAI capabilities and scaling its impact across global markets.
A successful Data Scientist at Amazon demonstrates bias for action and operates in a startup environment, with leadership skills, and proven ability to build and manage medium-scale modeling projects, identify data requirements, build methodology and tools that are statistically grounded. We need great leaders to think big and design new solutions to solve complex problems using machine learning (ML) and Generative AI techniques to improve our customers’ experience when using AB. You have hands-on experience making the right decisions about technology, models and methodology choices.
Key job responsibilities
As a Data Scientist, you will primarily leverage machine learning techniques and generative AI to outreach customers based on their life cycle stage, behavioral patterns, and purchase history. You may also perform text mining and insight analysis of real-time customer conversations and make the model learn and recommend the solutions. Your work will directly impact the trust customers place in Amazon Business.
You will partner with product management and technical leadership to identify opportunities to innovate customer journey experiences. You will identify new areas of investment and work to align product roadmaps to deliver on these opportunities. As a science leader, you will not only develop unique scientific solutions, but also play a crucial role in shaping strategies.
Additional responsibilities include:
- Ability to understand a business problem and the available data and identify what statistical or ML techniques can be applied to answer a business question
- Deliver artifacts on medium to large projects and experiments from beginning to end; and contribute solutions to complex and ambiguous problems.
- Use broad expertise to recommend the right strategies, methodologies, and solve challenges using statistical modeling, machine learning, optimization, and/or other approaches for quantifiable impact on the business
- Build models that measure incremental value, predict growth, define and conduct experiments to optimize engagement of AB customers, and communicate insights and recommendations to product, sales, and finance partners.
A day in the life
In this role, you will be a technical expert with significant scope and impact. You will work with Technical Product Managers, Data Engineers, other Scientists, and Salesforce developers, to build new and enhance existing ML models to optimize customer experience. You will prototype and test new ideas, iterate quickly, and deploy models to production. Also, you will conduct in-depth data analysis and feature engineering to build robust ML models.- Master's degree or above in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
- 2+ years of data scientist experience
- 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 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 managing data pipelines
- Experience working on personalisation and customer journey analysis
- Experience in building text/speech recognition, machine translation and natural language processing systems (e.g., emails, phone conversations)
- Experience building applications leveraging GenAI
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, 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.
