Worldwide Amazon Stores Finance Science (ASFS) leverage science and economics to drive improved financial results foster data driven decisions and embed science within Finance. ASFS is focused on developing science products that empower controllership improve business decisions and financial planning and innovate science capabilities for efficiency and scale.
We are looking for a data scientist to grow their skills in the entire machine learning lifecycle. The role will lead high visibility initiatives for controllership and financial anomaly detection. The ideal candidate will be an innovative problem solver with strong business acumen leveraging techniques such as machine learning statistics forecasting and large language models to transform Amazon Stores financial reporting and controllership capabilities. You are excited to learn from and alongside seasoned scientists engineers and business leaders. You are an excellent communicator and effectively translate technical findings into business action.
Key job responsibilities
Develop science models to help detect anomalous patterns in financial data using forecasting transformer and unsupervised methods.
Work with technical and nontechnical customers across every step of data science project life cycle.
Collaborate with our dedicated product data engineering and software development teams to create production implementations for largescale science applications.
Develop an understanding of key business metrics / KPIs and provide clear compelling analysis that shapes the direction of our business.
Present research results to our internal science community.
2 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
Masters degree or above in computer science mathematics statistics machine learning or equivalent quantitative field
Experience in Python Perl or another scripting language
Experience with AWS services including S3 Redshift Sagemaker EMR Kinesis Lambda and EC2
Experience with anomaly detection and/or predictive modeling.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees supervisors and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees supervisors and staff to ensure exceptional customer service; and follow all federal state and local laws and Company policies. Criminal history may have a direct adverse and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above as well as the abilities to adhere to company policies exercise sound judgment effectively manage stress and work safely and respectfully with others exhibit trustworthiness and professionalism and safeguard business operations and the Companys reputation. Pursuant to the Los Angeles County Fair Chance Ordinance we will consider for employment qualified applicants with arrest and conviction records.
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Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $125500/year in our lowest geographic market up to $212800/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on jobrelated knowledge skills and experience. Amazon is a total compensation company. Dependent on the position offered equity signon 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.