Data Scientist, Devices and Services FinTech

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 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. They are almost like FinTech consultants embedded in Amazon.

About This Role

The Amazon Devices and Services FinTech team is expanding our data science team that is building a forecasting solution 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, 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

1. 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.
2. Continuously innovate through research and the application of the latest machine learning techniques to drive forecasting accuracy improvement.
3. Perform exploratory data analysis to identify business opportunities and develop a plan to address them.
4. 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.
5. Build customer-facing reporting tools to provide insights and metrics which track forecast performance and explain variance.
6. Utilize code (Python, R, Scala, SQL, etc.) for analyzing data and building statistical and machine/deep learning models.

A day in the life

In a typical day as a data scientist at Amazon FinTech, you'll begin by delving into complex datasets, applying your technical expertise in feature engineering and exploratory data analysis to uncover valuable insights. You'll utilize both traditional time series forecasting techniques as well as more advanced machine learning algorithms to build accurate and reliable forecasting models that solve complex business problems like Operational Expense (OpEx) Forecasting. Collaboration with business, engineering, and partner teams is essential, as you'll translate your data-driven forecasts into actionable insights that align with strategic goals. Throughout the day, you'll innovate by adapting new forecasting methods, ensuring your solutions are stable, scalable, and fault-tolerant. Your strong communication skills and attention to detail will help you manage and integrate large datasets, solve unstructured problems, and drive projects to completion in a fast-paced, dynamic environment.

Join us and be a part of our dynamic team, driving the future of financial technology at Amazon.

Basic Qualifications

1. Bachelor's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science.
2. 3+ years of data scientist experience.
3. 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.
4. 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience.
5. Experience applying theoretical models in an applied environment.

Preferred Qualifications

1. Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science.
2. Experience in Python, Perl, or another scripting language.
3. 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. For individuals with disabilities who would like to request an accommodation, please visit .

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 . This position will remain posted until filled. Applicants should apply via our internal or external career site.

Company - Amazon.com Services LLC

Job ID: A2714899