ML Engineer
4 weeks ago
Job Description: Client Engineer
FEP Local systems provides Machine Learning service to FEP Client plans to improve claim processing, provider prediction, and automation that reducing human intervention process. As extension of Client services to other business cases and additional plans who joined to this service, we need resources to help to development Client program with FEP Local development team.
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 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
EEO:
"Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of - Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans."
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