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Amazon Data Scientist III Creative X - RAPID 
United States, New York, New York 
266180387

27.01.2025
DESCRIPTION

Data ScientistKey Responsibilities:Design and execute end-to-end data science projects, from problem definition to solution deploymentCreate and maintain data pipelines for model training and deployment
Conduct exploratory data analysis to uncover patterns and trends
Collaborate with stakeholders to understand business requirements and translate them into technical solutions
Present findings and recommendations to technical and non-technical audiences
Monitor and optimize model performance
Key job responsibilities* Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, perform hands-on analysis and modeling of enormous data sets to develop insights that improve shopper experiences and merchandise sales
* Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity.
* Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models.
* Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.
* Research new and innovative machine learning approaches.
* Promote the culture of experimentation and data science at Amazon

BASIC QUALIFICATIONS

- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 4+ years of industry or academic research experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing


PREFERRED QUALIFICATIONS

- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.