Prime Video is an industry leading, high-growth business and a critical driver of Amazon Prime subscriptions, which contribute to customer loyalty and lifetime value. Prime Video is used daily by a massive audience on Amazon’s websites and through a variety of devices including the Kindle Fire, game consoles, smart TVs and Blu-ray players. Prime Video is a digital video streaming and download service that offers Amazon customers the ability to rent, purchase or subscribe to a huge catalog of videos. Movies range from new releases to classic favorites with subscription or purchase, and Prime Video offers major television seasons, live sports, and access to more Channels.
The Prime Video Programming team owns the strategic perspective on overall programming and scheduling across originals and licensing. The group delivers consumer insights, constructs audience strategies, builds the portfolio, and schedules originals and licensed programs to drive service-level customer acquisition, engagement, and retention.
We are seeking a truly innovative Data Scientist to guide our segmentation strategy and build new solutions that allow us to understand existing and future customers better. As a Data Scientist on this team, you will have the opportunity to work on one of the world’s largest consumer data sets and influence the long term evolution of our analytics capability.
This role requires a team member with strong quantitative modeling skills and the ability to apply statistical/machine learning methods to large amount of individual level and title level data. The candidate should have strong communication skills and be able to work closely with stakeholders and translate data-driven findings into actionable insights. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail and ability to work in a fast-paced and ever-changing environment.
On our team you will work as the lead Data Scientist on a team of business owners and Product Managers, Business Intelligence Engineers, and Data Engineers. You will work in close collaboration with central Data Science and Economics teams who also support the organization’s mission.
We are open to hiring candidates to work out of one of the following locations:
Culver City, CA, USA | Seattle, WA, USA
BASIC QUALIFICATIONS
– MS in Mathematics, Statistics, Machine Learning, or a related quantitative field and 8+ years of experience or BS in Mathematics, Statitics, Machine Learning, or related quantitative field and 11+ years of experience
– Deep understanding and practical experience in several of the following areas: machine learning, statistics, NLP, deep learning, recommendation systems, dialogue systems, information retrieval.
PREFERRED QUALIFICATIONS
– Extensive experience applying theoretical models in an applied environment
– Strong fundamentals in problem solving, algorithm design and complexity analysis
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 $145,800/year in our lowest geographic market up to $294,700/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.