Responsibilities:
Develop AI and Generative AI models and solutions using AWS Sagemaker.
Evaluate, select, implement, and support an enterprise data science toolkit, ensure that systems are reliable, scalable, and maintainable
Build consensus around standards and best practices while ensuring alignment with enterprise principles
Use statistical and machine learning techniques to analyze data and develop predictive models
Communicate insights and findings to both technical and non-technical audiences
Develop and deploy processes to automate data ingestion, preparation, model training, predictions, and data delivery
Monitor the performance of machine learning models and make improvements as needed
Discover the information hidden in vast amounts of data, and help with making smarter decisions to deliver even better products.
Apply data mining techniques, perform statistical analysis, and build high quality prediction systems integrated with products.
Explore, promote, and implement semantic data capabilities through Natural Language Processing, text analysis and Machine Learning techniques.
Attend status and projects meetings to discuss, schedule, prioritize tasks, and report progress of projects
Requirements:
Bachelor s Degree in Computer Science or related field
3 years of experience in a Data Scientist or Machine Learning Engineer role required
Must have more than one year of AWS Sagemaker experience.
Experience with implementation of AWS Services preferred such as Lambda, S3, and AppFlow.
Knowledge of SQL. Experience with Snowflake desirable.
Proven track record of supporting high quality data science processes or applications
Highly developed problem-solving and troubleshooting skills
Ability to interact effectively with peers in a transparent manner
Ability to perform various data sourcing, transformation, and storage tasks
Knowledge of statistical based data analysis and developing machine learning models
Extensive Python usage
Experience with deploying and monitoring machine learning models
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