Cynet Systems

Data Scientist / Machine Learning Engineer

Job description

Job Description:

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.
  • Client 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 is 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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