Senior Data Scientist

3 weeks ago

London, Greater London, United Kingdom Amazon Full time

About the Role

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As a Senior Machine Learning Scientist at Amazon, you will be responsible for developing data-driven decision processes from historical data and ML-based predictive analysis. You will maintain accurate and reliable data infrastructure, working with big data, developing insightful analysis, and communicating findings in a clear and compelling way.

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We are looking for highly technical and analytical individuals with 7+ years of experience in Machine Learning and/or Analytics Systems development and deployment. You should possess significant experience in software development, IT systems, and engineering, as well as security and compliance expertise.

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Your responsibilities will include:

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  • Developing and implementing machine learning models to predict inbound capacity forecasts and select the optimal order of unloading and stowing incoming items.\
  • Utilizing advanced machine learning and cloud computing techniques to power Amazon's operations performance management.\
  • Leveraging big data analytics to extract insights and deliver recommendations to operations managers.\
  • Maintaining accurate and reliable data infrastructure.\
  • Communicating findings in a clear and compelling way.\
  • Working effectively as part of the team, raising the bar, and insisting on high standards.\
  • Leading large-scale big data and analytics projects.\
  • Architecting, deploying, and maintaining production machine learning systems.\
  • Demonstrated industry leadership in Big Data processing, Data Sciences, and Machine Learning.\
  • Deep understanding of data, application, server, and network security.\
  • Experience with Statistics, Machine Learning, and Predictive Modelling.\
  • Working knowledge of modern software development practices and technologies such as agile methodologies and DevOps/MLOps.\
  • AWS Certification, eg. AWS Solutions Architect, Developer, or AWS Certified Machine Learning - Specialty.\
  • Knowledge of foundation infrastructure requirements such as Networking, Storage, and Hardware Optimisation.\
  • Experience with implementation and tuning in the Big Data Ecosystem, (such as EMR, Hadoop, Spark, R, Presto, Hive), ML Platforms (SageMaker, Kubeflow, Azure Machine Learning, SAS, Domino), and MLOps (model development, orchestration and deployment, monitoring, optimisation).\
  • Track record of implementing AWS services in a variety of business environments such as large enterprises and start-ups.\
  • Hands-on experience leading large-scale big data and analytics projects.\
  • Hands-on experience as a database, data warehouse, big data/analytics developer or administrator, or work as a data scientist.\
  • Strong verbal and written communications skills are a must, as well as the ability to work effectively across internal and external organizations and virtual teams.\
  • Estimated salary: $150,000 - $200,000 per year.

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