Senior Manager, Applied Science, Sponsored Products
DESCRIPTION
Search Thematic Ad Experience (STAX) team within Sponsored Products is looking for a leader to lead a team of talented applied scientists working on cutting-edge science to innovate on ad experiences for Amazon shoppers!. You will manage a team of scientists, engineers, and PMs to innovate new widgets on Amazon Search page to improve shopper experience using state-of-the-art NLP and computer vision models. You will be leading some industry first experiences that has the potential to revolutionize how shopping looks and feels like on Amazon, and e-commerce marketplaces in general. You will have the opportunity to design the vision on how ad experiences look on Amazon search page, and use the combination of advanced techniques and continuous experimentation to realize this vision. Your work will be core to Amazon’s advertising business. You will be a significant contributor in building the future of sponsored advertising, directly impacting the shopper experience for our hundreds of millions of shoppers worldwide, while delivering significant value for hundreds of thousands of advertisers across the purchase journey with ads on Amazon.
Key job responsibilities
* Be the technical leader in Machine Learning; lead efforts within the team, and collaborate and influence across the organization.
* Be a critic, visionary, and execution leader. Invent and test new product ideas that are powered by science that addresses key product gaps or shopper needs.
* Set, plan, and execute on a roadmap that strikes the optimal balance between short term delivery and long term exploration. You will influence what we invest in today and tomorrow.
* Evangelize the team’s science innovation within the organization, company, and in key conferences (internal and external).
* Be ruthless with prioritization. You will be managing a team which is highly sought after. But not all can be done. Have a deep understanding of the tradeoffs involved and be fierce in prioritizing.
* Bring clarity, direction, and guidance to help teams navigate through unsolved problems with the goal to elevate the shopper experience. We work on ambiguous problems and the right approach is often unknown. You will bring your rich experience to help guide the team through these ambiguities, while working with product and engineering in crisply defining the science scope and opportunities.
* Have strong product and business acumen to drive both shopper improvements and business outcomes.
A day in the life
* Lead a multidisciplinary team that embodies “customer obsessed science”: inventing brand new approaches to solve Amazon’s unique problems, and using those inventions in software that affects hundreds of millions of customers
* Dive deep into our metrics, ongoing experiments to understand how and why they are benefitting our shoppers (or not)
* Design, prototype and validate new widgets, techniques, and ideas. Take end-to-end ownership of moving from prototype to final implementation.
* Be an advocate and expert for STAX science to leaders and stakeholders inside and outside advertising.
About the team
We are the Search thematic ads experience team within Sponsored products - a fast growing team of customer-obsessed engineers, technologists, product leaders, and scientists. We are focused on continuous exploration of contexts and creatives to drive value for both our customers and advertisers, through continuous innovation. We focus on new ads experiences globally to help shoppers make the most informed purchase decision while helping shortcut the time to discovery that shoppers are highly likely to engage with. We also harvest rich contextual and behavioral signals that are used to optimize our backend models to continually improve the shopper experience. We obsess about our customers and are continuously seeking opportunities to delight them.
We are open to hiring candidates to work out of one of the following locations:
New York, NY, USA
BASIC QUALIFICATIONS
* Master's Degree in applied research (machine learning, recommender systems, statistics, computer science, operations research or other highly relevant field)
* 10+ years of experience applying ML to solve complex problems for large-scale applications and 3+ years of experience managing Scientists and Engineers
* Ability to translate informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
PREFERRED QUALIFICATIONS
* Ph.D. in Computer Science, Machine Learning, Statistics, Applied Mathematics, or a closely related field.
* Demonstrated leadership abilities, especially with cross-disciplinary efforts.
* Project management experience.
* Excellent written and verbal communication skills with the ability to present complex technical information in a clear and concise manner to a variety of audiences.
* Previous experience in advertising is a plus.
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 $175,000/year in our lowest geographic market up to $340,300/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.