Senior Applied Scientist (AI)

Location: USA, New York

Salary: $183,800–$248,700 annually, plus sign-on payments and restricted stock units.

Company

Amazon Ads develops advertising products and measurement solutions that help advertisers understand and optimize the impact of their media investments.

What you will do

• Develop scalable ad measurement models covering online and offline sales, multiple platforms, and different timescales.
• Design, analyze, test, and productionize machine learning and statistical models.
• Apply generative AI, classical machine learning, causal inference, natural language processing, and computer vision.
• Partner with engineering, product management, business teams, sales leaders, and scientists to deploy solutions and enable advertiser action.
• Generate insights from large datasets, design simulations and experiments, and present findings to technical and non-technical audiences.
• Mentor junior scientists and contribute to scientific collaborations, presentations, publications, and patents.

Requirements

• 3+ years of experience building machine learning models for business applications.
• PhD, or a master's degree with 6+ years of applied research experience.
• Experience programming in Python, Java, C++, Perl, or a related language.
• Experience with neural deep learning methods and machine learning.
• Ability to collaborate with scientists, engineers, product managers, and business stakeholders.

Nice to have

• Experience with R, scikit-learn, Spark MLlib, MxNet, TensorFlow, NumPy, or SciPy.
• Experience with large-scale distributed systems such as Hadoop or Spark.

Culture & Benefits

• Work with scientists across applied science, research, data science, and economics.
• Collaborate with specialists in machine learning, NLP, computer vision, generative AI, and causal inference.
• Health, dental, vision, prescription, life, and mental health benefits.
• 401(k) matching, paid time off, parental leave, and flexible spending accounts.
• Disability accommodations are available during the application and hiring process.