Amazon Senior Applied Scientist WW Ops Finance & 

United States, Texas, Dallas 

537947405

Key job responsibilities- Drive and lead strategic initiatives to employ the most recent advances in ML/AI in a fast-paced, experimental environment- 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.).

- 5+ years of building Machine Learning, Generative AI, Natural Language Processing/Understanding, Reinforcement learning models for business application experience
- PhD in one of the following disciplines: 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
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.