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Senior Applied Scientist, WW Ops Finance S&A

Amazon

$150,400 - $260,000
Apr 15, 2025
Dallas, TX, US
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Transforming the way Operations Finance teams create and bridge financial plans, consume insights, identify root causes and prepare XBRs through a combination of Generative AI, Machine Learning and Economic models.

Requirements

  • 5+ years of building Machine Learning, Generative AI, Natural Language Processing/Understanding, Reinforcement learning models for business application experience
  • PhD in Computer Science, Machine Learning, Statistics, Data Science, Applied Math, Operational Research or a related quantitative field
  • Fluency in Python, SQL or similar scripting languages and skilled at Java, C++, or other programing languages
  • Experience with Machine Learning Pipeline orchestration with AWS (SageMaker, Batch, Lambda, Step Functions) or similar cloud-platforms
  • Depth and breadth in state-of-the-art Generative AI and machine learning technologies
  • Publications at top-tier peer-reviewed conferences or journals in one of those areas (natural language processing/understanding, deep learning, machine learning, or speech processing)
  • Experience in Big Data Engineering with Spark / AWS EMR & Glue

Responsibilities

  • Design, architecture, and implementation of AI/ML products
  • Drive and lead strategic initiatives to employ the most recent advances in ML/AI
  • Collaborate with business, product and engineering stakeholders to innovate on behalf of customers leveraging data science methodologies
  • Adapt statistical and machine learning methodologies for Ops Finance by developing and testing models, running computational experiments, and fine-tuning model parameters
  • Develop code to analyze data (SQL, PySpark, Scala, etc.) and build statistical and machine learning models and algorithms (Python, R, Scala, etc.)
  • Mentor and grow the scientists in the team

Other

  • Communicate verbally and in writing to business and internal stakeholders with various levels of technical knowledge
  • Educate stakeholders on our research and data science practice, and deliver actionable insights and recommendations
  • 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