Data Scientist, Devices and Services FinTech

Amazon • Seattle, WA

62d

About The Position

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.

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.

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.

Requirements

• 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

Nice To Haves

• 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

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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level