Data Science Manager

Full time

Employment Information

Job levelSenior level

Salary$140 100 - $272 400

IndustrySoftware Development

Experience5+ years

LocationBellevue, WA, United States

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Description

Are you excited about developing generative AI and foundation models to revolutionize automation, robotics and computer vision? Are you looking for opportunities to build and deploy them on real problems at truly vast scale? At Amazon Fulfillment Technologies and Robotics we are on a mission to build high-performance autonomous systems that perceive and act to further improve our world-class customer experience - at Amazon scale. We are looking for scientists, engineers and program managers for a variety of roles.

To this end, the Amazon Fulfillment Technology AI Team is looking for a data science manager to lead and grow a team of talented and experienced data scientists and business analysts who work cross-functionally, ensuring that we’re using data effectively and creatively to analyze, explore, and infer from large datasets in our warehouses. A successful candidate has a diverse analytic background, a deep curiosity for successful business operations, and an inventive spirit to develop models, insights, and prototypes that make a real difference for customers and for our business. They will have proven experience in applied analytics and be well-versed in modern tools and frameworks for data science and business analysis.

Key job responsibilities

In this role you will manage a team of data scientists, identify opportunities and develop data science strategies. You will work closely with teams of applied scientists, software engineers, and product managers to help extract insights from data to inform customer-level (and company-wide) investments and interventions intended to improve fulfillment center operations. You will ensure data quality throughout all stages of acquisition and processing, including such areas as data sourcing/collection, ground truth generation, normalization, transformation, etc. You will apply state-of-the-art approaches to statistical modeling, machine learning, and analytics, serving as the front line of statistically analyzing and visualizing our data and bringing its insights to life. You will communicate proposals and results in a clear manner backed by data and coupled with actionable conclusions to drive business decisions. You will manage your own process; prioritize and execute on high impact projects, triage external requests, and ensure to deliver projects in time.

A day in the life

Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include:

Medical, Dental, and Vision Coverage
Maternity and Parental Leave Options
Paid Time Off (PTO)
401(k) Plan

If you are not sure that every qualification on the list above describes you exactly, we’d still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!

About the team

Amazon Fulfillment Technologies (AFT) powers Amazon’s global fulfillment network. We invent and deliver software, hardware, and data science solutions that orchestrate processes, robots, machines, and people. We harmonize the physical and virtual world so Amazon customers can get what they want, when they want it.

The AFT AI team has deep expertise developing cutting edge AI solutions at scale and successfully applying them to business problems in the Amazon Fulfillment Network. These solutions typically utilize machine learning and computer vision techniques, applied to text, sequences of events, images or video from existing or new hardware. We influence each stage of innovation from inception to deployment, developing a research plan, creating and testing prototype solutions, and shepherding the production versions to launch.

We are open to hiring candidates to work out of one of the following locations:

Bellevue, WA, USA

Basic qualifications

5+ years of building quantitative solutions as a scientist or science manager experience
2+ years of scientists or machine learning engineers management experience
5+ years of applying statistical models for large-scale application and building automated analytical systems experience
PhD in computer science, mathematics, statistics, machine learning or equivalent quantitative field

Preferred qualifications

Experience in a least one area of Machine Learning (NLP, Regression, Classification, Clustering, or Anomaly Detection)
Experience with fairness in machine learning and artificial intelligence to detect and remove bias in ML/AI systems

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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $140,100/year in our lowest geographic market up to $272,400/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. Applicants should apply via our internal or external career site.