CASY-MSCCN Jobs

Description

Join our Amazon Private Brands Selection Guidance organization in building science and tech solutions at scale to delight our customers with products across our leading private brands such as Amazon Basics, Amazon Essentials, and by Amazon.

The Selection Guidance team applies Generative AI, Machine Learning, Statistics, and Economics solutions to drive our private brands product assortment, strategic business decisions, and product inputs such as title, price, merchandising and ordering. We are an interdisciplinary team of Scientists, Economists, Engineers, and Product Managers incubating and building day one solutions using cutting-edge technology, to solve some of the toughest business problems at Amazon.

As a Product Manager - Technical in Selection Guidance you work backwards from the needs of the business to bring structure to ambiguous problems. You set the vision for your product space and outline a roadmap that delivers incremental value to the business as you work towards the product vision. You have a clear understanding of business needs and impact, and use that knowledge to define clear product priorities. Data is at the heart of our solutions, and you dive deep into the data and details of your problem space and collaborate with scientists to frame ambiguous problems into science and tech solutions.

This is a unique, high visibility opportunity for someone who wants to have business impact, dive deep into large-scale science problems, enable measurable actions on the Consumer economy, and work closely with scientists and economists. If you are interested in Machine Learning, Generative AI, and large-scale intelligent solutions then this is the role you have been looking for.

Key job responsibilities

As a PMT on this team, you will:

• Lead the vision, strategy, and execution of new ML-driven systems that suggest new products and identify key improvement opportunities for existing products.

• Collaborate with groups of experts and cross-functional colleagues in an agile environment.

• Learn and grow by being exposed to multiple organizational challenges in a short time frame.

• Work with business leaders, scientists, and economists to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable distributed services.

• Partner with scientists, economists, and engineers to help deliver scalable ML and econometric models while building tools to help our customers gain and apply insights.

• Dive deep into the data behind historical product launches and product performance to uncover patterns, identify success metrics, and track the performance of your new systems.

• You will be responsible for disrupting traditional business process in order to create the agility necessary to develop and incubate new solutions to challenging business problems.

• You will draw from a deep and broad technical expertise to own large and complex multi-business deliverables.

A day in the life

• You take advantage of the morning time zone overlap to sync virtually with Hardlines product owners in London. You check in on their experience utilizing your new system and ask about their other challenges to help inform future big ideas

• You participate in a quick tech standup with Scientists and Engineers working to build your next system. You help unblock an Engineer by clarifying a requirement, and take an action item to provide feedback on a Scientist's draft proposal.

• You spend some focused time diving into the adoption data for your latest release. You identify one specific anecdote to address with a stakeholder, you define how you want to track successful adoption, and create a task for an engineer to automate your prototype metric.

• You attend a design review for a new internal UI for your system and provide feedback to the Engineer given your grasp on both the customer experience and technical complexities.

• You present a document to senior leadership proposing your new system, with a customer experience, tech roadmap, and key requests from business teams.

About the team

We are a Day 1 team, with a charter to be disruptive through the use of Data Science and Machine Learning. We immerse ourselves in the Amazon Basics products to understand our customers and partners, we stay abreast of the evolving state-of-the-art in Machine learning, and we value moving quickly to prototype solutions. The team is primarily located in San Diego and Seattle. Outside our immediate team, we partner closely with Softlines, Hardlines, and Consumables business owners.

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

San Diego, CA, USA | Seattle, WA, USA

Basic Qualifications

• Bachelor's degree

• Experience owning/driving roadmap strategy and definition

• Experience with feature delivery and tradeoffs of a product

• Experience contributing to engineering discussions around technology decisions and strategy related to a product

• Experience managing technical products or online services

• Experience in representing and advocating for a variety of critical customers and stakeholders during executive-level prioritization and planning

• Data-driven decision making and quantitative analysis skills, including deep knowledge of statistical analysis, Excel, SQL and/or other analytical techniques.

Preferred Qualifications

• Master's degree

• Experience bridging technical and business teams to collect and refine requirements, prioritize incoming work requests, and ensure all committed work is delivered on time

• Experience in building and driving adoption of new tools

• Superior analytical and quantitative skills; experience using Machine Learning and/or Generative AI to solve problems.

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 $121,000/year in our lowest geographic market up to $235,200/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.