Data Scientist, Devices and Services FinTech
Amazon
26.11.2025
ABD
Deneyim: 2-4 Yıl
Çalışma Şekli: Tam Zamanlı
Çalışma Konumu: Uzaktan
Departman Seviyesi: Uzman
İlan Açıklaması
Description
Are you looking for an opportunity to own a large-scale technology problem? Do you enjoy finding patterns and pushing the boundaries of current possibilities? Are you interested in building reliable and scalable systems that support Amazon's growth? If so, Amazon Devices and Services Finance Technology (FinTech) is the perfect place for you!
ABOUT THIS ROLE
The Amazon Devices and Services FinTech team is expanding our data science team that is building forecasting solutions and advanced analytics platforms for the Amazon Devices and Services Finance organization, and we are looking for a Data Scientist to join us. As a data scientist, you will dive deep into data from across Amazon's finance organization, extract new insights, drive investigations and algorithm development, and interface with technical and non-technical customers. You will leverage your data science expertise and communication skills to pivot between delivering science solutions, translating knowledge of finance and operational processes into forecasting models, building product analytics for our AI systems, and communicating insights and recommendations to audiences of varying levels of technical sophistication in support of specific business questions, root cause analysis, planning, and innovation for the future.
Key job responsibilities
- Create various forecasts, including but not limited to Operational Expenses, and drive adoption of these forecasts by various teams within Amazon for financial and operations planning
- Build product metrics, monitoring pipelines, and analytics tools for our AI assistant to track performance, user engagement, and system reliability
- Continuously innovate through research and the application of the latest machine learning techniques to drive forecasting accuracy improvement and AI system optimization
- Perform exploratory data analysis to identify business opportunities and develop plans to address them across both financial forecasting and AI product development
- Communicate verbally and in writing to business customers with various levels of technical knowledge, educating them about our systems, as well as sharing insights and recommendations
- Build customer-facing reporting tools and dashboards to provide insights and metrics which track forecast performance, AI assistant effectiveness, and explain variance
- Utilize code (Python, R, Scala, SQL, etc.) for analyzing data and building statistical and machine/deep learning models for both financial forecasting and AI product analytics
A day in the life
As a data scientist at Amazon Devices and Services FinTech, you'll dive into complex datasets using advanced analytics and machine learning to build accurate forecasting models for problems like Operational Expense forecasting. You'll also develop product metrics and monitoring pipelines for our AI assistant, analyzing user engagement and system performance. Collaboration with business and engineering teams is essential as you translate insights into actionable recommendations. Throughout the day, you'll innovate by adapting new forecasting methods and AI analytics approaches, ensuring solutions are scalable and reliable. Your communication skills help you solve unstructured problems in our fast-paced, dynamic environment.
About the team
Amazon Devices and Services FinTech is the global team that designs and builds the financial planning and analysis tools for a wide variety of Devices' new and established organizations. From Kindle to Ring and even new and exciting companies like Kuiper (our new interstellar satellite play), this team enjoys a wide variety of complex and interesting problem spaces. We also own and operate the organization's AI assistant, making us true FinTech innovators embedded within Amazon.
Basic Qualifications
- Bachelor's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
- 3+ 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
Preferred Qualifications
- Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
- Experience in Python, Perl, or another scripting language
- Experience in a ML or data scientist role with a large technology company
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Aday Kriterleri
Eğitim Durumu: Lisans
Dil Bilgisi: İngilizce
Askerlik Durumu: Farketmez
Üniversite Bölümü: Tüm departmanlar
Yetenekler
Şirket Hakkında
Amazon Hakkında
Amazon is guided by four principles: customer obsession rather than competitor focus, passion for invention, commitment to operational excellence, and long-term thinking. We are driven by the excitement of building technologies, inventing products, and providing services that change lives. We embrace new ways of doing things, make decisions quickly, and are not afraid to fail. We have the scope and capabilities of a large company, and the spirit and heart of a small one. Together, Amazonians research and develop new technologies from Amazon Web Services to Alexa on behalf of our customers: shoppers, sellers, content creators, and developers around the world. Our mission is to be Earth's most customer-centric company. Our actions, goals, projects, programs, and inventions begin and end with the customer top of mind. You'll also hear us say that at Amazon, it's always "Day 1." What do we mean? That our approach remains the same as it was on Amazon's very first day - to make smart, fast decisions, stay nimble, invent, and focus on delighting our customers.
