Principal Data Scientist, Prime Video - Discovery ScienceJob ID: 2662708 | Amazon.com Services LLC
Are you interested in shaping the future of entertainment? Prime Video's mission is to be the #1 entertainment destination for customers worldwide and Prime Video's technology teams are creating best-in-class digital video experience.
As a Prime Video technologist, you'll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You'll get to work on projects that are fast-paced, challenging, and varied. You'll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people.
We'll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers.
Key job responsibilities
The Principal Data Scientist (DS) on this team is a technical expert and strategic thought leader responsible for tackling highly complex and ambiguous problems. They lead the charge in translating Prime Video's mission into organizational north-star goals, shaping the product and engineering mental models around causal success measurement, and having a long-lasting influence on the product and engineering roadmap.
A successful candidate will have proven expertise in statistical modeling, machine learning, and experiment design, along with a solid practical understanding of the strengths and weaknesses of various scientific approaches. They excel at deep diving into complex problems, driving innovative scientific solutions, and effectively communicating key takeaways to influence business and product decisions. They set best practices for data-driven decision-making and advise on high-judgment decisions with competing interests.
As a strategic Principal Scientist, you will interact frequently with senior leadership, identify investment opportunities, develop long-term strategies, and propose, influence prioritization, and deliver on goals. You will define organizational success measures and be technically fearless with a passion for building scalable science and engineering solutions. You will serve as a key scientific resource in full-cycle development, from conception and design to implementation, testing, documentation, delivery, and maintenance.
You will also play a pivotal role in career development and mentoring and actively contribute to the hiring process.
About the team
Prime Video discovery science is a central team which defines customer and business success metrics, models, heuristics and econometric frameworks. The team develops, owns and operates a suite of data science and machine learning models that feed into online systems that are responsible for personalization and search relevance. The team is responsible for Prime Video's experimentation practice and continuously innovates and upskills teams across the organization on science best practices. The team values diversity, collaboration and learning, and is excited to welcome a new member whose passion and creativity will help the team continue innovating and enhancing customer experience.
BASIC QUALIFICATIONS• MS in Mathematics, Statistics, Machine Learning, or a related quantitative field, or equivalent 10+ years of practical experience applying modeling or machine learning to solve complex problems for large-scale applications
• 7+ years industry experience building successful production science solutions
• Deep understanding and practical experience in several of the following areas: machine learning, statistics, causal inference and recommendation systems
• Excellent problem-solving skills with the ability to design algorithms, which may include data profiling, clustering, anomaly detection, predictive modeling methodologies and more
• Excellent verbal and written communication skills with the ability to effectively advocate technical solutions to research scientists, engineering teams and business audiences.
PREFERRED QUALIFICATIONS• PhD in Mathematics, Statistics, Machine Learning, or a related quantitative field
• Experience in data applications using large scale distributed systems (e.g. EMR, Spark, Elasticsearch, Hadoop, Pig, Hive) and AWS platforms such as S3, Glue, Athena, Sagemaker.
• Previously held a technical leadership role for several complete large-scale initiatives.
Posted: November 23, 2024 (Updated about 3 hours ago)
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