Data Scientist, Managed Operations - Managed Operations Intelligence (MOI) Team
Amazon
Data Scientist, Managed Operations - Managed Operations Intelligence (MOI) Team
Job Description
Amazon Web Services (AWS) is the world leader in providing a highly reliable, scalable, low-cost infrastructure platform in the cloud that powers hundreds of thousands of businesses in 190 countries around the world! The AWS Managed Operations Intelligence (MOI) Team is looking for a Data Scientist to lead the research and thought leadership to drive our data and insight strategy for AWS. You will be expected to execute as a Full Stack Data Scientist. You will be responsible for driving data-driven transformation across the organization. In this role, you will be responsible for the end-to-end data science lifecycle, from data exploration, ETL, model development and data visualization. You will leverage a diverse set of tools and technologies, including general analytical frameworks (Spark, Airflow, etc.), AI frameworks (Hugging Face, etc.) and various machine learning frameworks, to tackle complex business problems. This position requires that the candidate selected be a U.S. citizen. Key job responsibilities - Work with large and complex data sets to solve a wide array of challenging problems using different analytical approaches - Develop ML/AI models. Partner with software teams to productionalize these models. - Data Pipeline and Infrastructure: design and implementation of data pipelines - Metric Development and Monitoring: Define and develop advanced, customized metrics and key performance indicators (KPIs) that capture the nuances of the organization's strategic objectives and operational complexities. - Continuously monitor and evaluate the performance of metrics About the team The Managed Operationsorganization reduces operational burden for AWS builders by executing long-term engineering projects. The Data Science team (MOI) harnesses the power of data science to identify operational trends across AWS to enable high-leverage decisions for our development teams to eliminate operational burden. The MOI team provides high leverage analytics to drive product strategy. We do this with a 'last mile' analytics service that integrates disparate data sources to solve business problems. We apply our knowledge of the semantic meaning of data and the underlying business processes that the data supports, to create advanced analytics solutions.
Locations
- Arlington, Virginia, United States
Salary
136,000 - 184,000 USD / yearly
Skills Required
- machine learning conceptsintermediate
- Pythonintermediate
- definingintermediate
Required Qualifications
- 2+ years of data scientist experience (experience, 2 years)
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience (experience, 3 years)
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience (experience, 3 years)
- 1+ years of guiding and coaching a group of researchers experience (experience, 1 years)
- 1+ years of working with or evaluating AI systems experience (experience, 1 years)
- 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience (experience, 1 years)
- Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM) (experience)
- Experience applying theoretical models in an applied environment (experience)
Preferred Qualifications
- Ph.D. in Science, Technology, Engineering, or Mathematics (STEM) (experience)
- Knowledge of machine learning concepts and their application to reasoning and problem-solving (experience)
- Experience in Python, Perl, or another scripting language (experience)
- Experience in a ML or data scientist role with a large technology company (experience)
- Experience in defining and creating benchmarks for assessing GenAI model performance (experience)
- Experience applying quantitative analysis to solve business problems and making data-driven business decisions (experience)
- Experience effectively communicating complex concepts through written and verbal communication (experience)
Responsibilities
- Work with large and complex data sets to solve a wide array of challenging problems using different analytical approaches
- Develop ML/AI models. Partner with software teams to productionalize these models.
- Data Pipeline and Infrastructure: design and implementation of data pipelines
- Metric Development and Monitoring: Define and develop advanced, customized metrics and key performance indicators (KPIs) that capture the nuances of the organization's strategic objectives and operational complexities.
- Continuously monitor and evaluate the performance of metrics
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