DESCRIPTION

Are you passionate about solving unique customer-facing problems in the Amazon scale? Are you excited about utilizing statistical analysis, machine learning, data mining and leverage tons of Amazon data to learn and infer customer shopping patterns? Do you enjoy working with a diversity of engineers, machine learning scientists, product managers and data analysts? If so, you have found the right match!

Fashion is extremely fast-moving, visual, subjective, and it presents numerous unique problem domains such as product recommendations, product discovery and evaluation. Amazon Fashion drives multiple core and advance science initiatives. The approach and technology are nothing short of disruptive, and promise to challenge traditional approaches, and change the way the industry operates.

We are hiring a Senior Data Scientist (DS) to help us accelerate our efforts in improving Amazon Fashion as part of a centralized Fashion Intelligence team. We are hiring a Data Scientist who has a strong background in causal inference and a proven record of effectively analyzing large complex heterogeneous datasets, and is motivated to grow professionally as a Data Scientist. The person in this role will work with economists, finance, CBA and business owners to define the right metrics and methodologies to compute attributed and incremental value of programs and features, while leveraging existing frameworks wherever applicable. They will innovate and develop solutions to ensure we have an understanding of the short and long term impact of the unique customer experience created by Fashion CX. The ideal candidate will be passionate about working with big data sets and have the expertise to utilize these data sets to derive insights, answer business questions and drive growth.

Key job responsibilities
You will work on our Fashion Intelligence to answer complex problems focusing on measuring the incremental impact of our programs on business performance. Outputs from your analysis will directly help improve the performance of various Fashion Tech programs.

Use analytical and statistical rigor to solve complex problems and drive business decisions that will help us achieve our strategic goals.

You have excellent communication skills to be able to work with cross-functional team members to understand key questions and earn the trust of senior leaders.

You are able to multi-task between different tasks such as understanding attribution and conversion across programs, integrating multiple disparate datasets, doing business intelligence, analyzing engagement metrics or presenting to stakeholders.

You thrive in an agile and fast-paced environment on highly visible projects and initiatives. We will look to this person to provide thought leadership with a lens across programs. The successful candidate will demonstrate strong business acumen, strong communication skills, and an ability to work effectively with cross functional teams.

About the team
The Fashion Tech organization has a mission to make Amazon the most-loved fashion destination globally through technology by building novel experiences that bring a diverse breadth of customers to shop fashion in the Amazon store. The Fashion Intelligence team improves the speed, accuracy, and standards of data driven decisions across all programs within Fashion Tech. Being specialists in the data lineage, we own building the right data infrastructure layer to enable reporting and analytics, while partnering with product teams in defining metrics, software engineering teams in instrumenting the appropriate data needed and data engineering in scaling our data warehouse. As a central analytics team, our goal is to break silos and identify interconnectedness across Fashion Tech programs, keeping the customer at the center.

BASIC QUALIFICATIONS

– 5+ 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+ years of data scientist experience
– Experience with statistical models e.g. multinomial logistic regression

PREFERRED QUALIFICATIONS

– 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
– Experience managing data pipelines
– Experience as a leader and mentor on a data science team

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 https://www.amazon.jobs/en/disability/us.

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 Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $143,300/year in our lowest geographic market up to $247,600/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.

USA, TX, Austin