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Data Scientist, Amazon Autos

Amazon

Amazon

Data Science
New York, NY, USA
Posted on Oct 18, 2024

DESCRIPTION

Interested in building something new? Join the Amazon Autos team on an exhilarating journey to redefine the vehicle shopping experience.
This is an opportunity to be part of the Amazon's new business ventures. Our goal is to create innovative automotive discovery and shopping experiences on Amazon, providing customers with greater convenience and a wider selection.
You'll work in a creative, fast-paced, and entrepreneurial environment at the center of Amazon's innovation. As a key member, you'll play a pivotal role in helping us achieve our mission. We are looking for a highly accomplished and visionary Data Science professional to lead our data science strategy, foster a culture of data-driven decision-making, and drive impactful business outcomes through advanced analytics and state-of-the-art data science methodologies.
If you are passionate about innovation, delivering exceptional customer experiences, and thrive in tackling new challenges, this role is for you. We seek someone with expertise in Statistical Analysis, Machine Learning, and Data Mining, with a proven ability to analyze large, complex, and diverse datasets. If you're motivated to grow professionally as a Data Scientist, you could be the ideal candidate for this opportunity
Join us on this exhilarating journey and be part of redefining the vehicle shopping experience.


Key job responsibilities
As a Data Scientist in Amazon Autos, you will:

* Develop and implement the data science strategy for Amazon Autos, ensuring it aligns with both program goals and broader business objectives.
* Leverage your skills in areas such as statistical analysis, deep learning, machine learning, and reinforcement learning to drive innovation and enhance the automotive shopping experience.
* Effectively analyze large, complex, and diverse datasets collected from diverse sources to derive key insights, build segmentation models and improve customer shopping experience.
* Utilize your Generative AI, time series and predictive modeling skills, and creative problem-solving skills to drive new projects from ideation to implementation.
* Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to define project requirements, establish success metrics, and deliver high-quality solutions.
* Design, develop, and evaluate innovative ML models to solve diverse obstacles and opportunities across business teams.
* Interface with business customers, gathering requirements and delivering science solutions.
* Effectively communicate complicated machine learning concepts to multiple partners.



A day in the life
In this role, you will be part of a multidisciplinary team working on one of Amazon's newest business ventures. As a key member, you will collaborate closely with engineering, product, design, operations, and business development to bring innovative solutions to our customers.
Your science expertise will be leveraged to research and deliver data-driven solutions to existing problems, explore emerging problem spaces, and create new knowledge. You will report updates and insights from your work to leadership. You will invent and apply state-of-the-art technologies, such as large language models, machine learning, natural language processing, and computer vision, to build next-generation solutions for Amazon.
You'll publish papers, file patents, and work closely with engineers to bring your ideas to production.
This is an opportunity to make a significant impact, working in partnership with teams across Amazon to create enormous benefits for our customers through cutting-edge products.


About the team
This is a critical role for a newly formed team with a vision to create innovative automotive discovery and shopping experiences on Amazon, providing customers better convenience and more selection. We’re collaborating with other experienced teams at Amazon to define the future of how customers research and shop for cars online.