Note: The job is a remote job and is open to candidates in USA. Centene Corporation is a diversified, national healthcare organization serving 28 million members and using technology to improve health outcomes. The Senior IT Data Scientist designs, develops, tests, deploys, and monitors scalable AI/ML and predictive modeling solutions, while partnering with internal customers to derive business insights and support operational analysis.

Responsibilities

• Participates in model brainstorming conversations with new potential internal customers interested in AI/ML capabilities
• Works alongside internal customers that are requesting AI/ML capabilities to understand overall business objective & impact when requesting an AI/ML model
• Analyzes use cases of ML algorithms and apply findings to enable business decisions by deriving insights through data visualization
• Writing moderately complex SQL and Python/R code to extract data from a variety of databases and data sources
• Explores and visualizes data to gain an understanding of it and verify data quality, and/or ensure data quality via data cleaning
• Conduct exploratory data analysis from complex data sources and build key data sets to support company mission operational analysis
• Builds ML/AI models using common methods within R and Python
• Analyzes the ML algorithms that could be used to solve a given problem and rank them by their success probability
• Analyzes errors of the model and design strategies to overcome errors
• Develop logging, alerting, and mitigation strategies for handling model errors
• Development of AI/ML models to distinguish relevant content or events and recognize patterns
• Designs and develops AI/ML models to predict member outcomes or future impact of key member decisions
• Evaluate and design experiments to monitor key model metrics and identify improvement opportunities
• Participate in presentations and communicate results of research analysis and findings to non-technical business partners
• Produces fairness review for each developed model, to ensure model is free of bias
• Set up continuous integration/continuous deployment (CI/CD) pipelines used for model automation
• Model deployment with containers such as Kubernetes and/or Docker
• Produce clean & readable code that has been properly unit tested and optimized for performance
• Completes proper deployment integration testing to ensure seamless deployment
• Maintains and supports AI/ML patterns by reviewing and solving issues and running ML/AI models
• Assists in leading team-wide initiatives that help develop templates and define best practices to improve model building and deployment workflow (ex. Model drift detection)
• Performs other duties as assigned
• Complies with all policies and standards

Skills

• A Bachelor's degree in a quantitative or business field (e.g., statistics, mathematics, engineering, computer science)
• 4 – 6 years of related experience
• 4+ years Intermediate knowledge & experience with SQL required
• 4+ years Experience in developing Machine Learning/AI/Predictive models in R or Python required
• 4+ years Intermediate knowledge of Git required
• Experience using Databricks Platform
• Writing moderately complex SQL and Python/R code to extract data from a variety of databases and data sources
• Explores and visualizes data to gain an understanding of it and verify data quality, and/or ensure data quality via data cleaning
• Conduct exploratory data analysis from complex data sources and build key data sets to support company mission operational analysis
• Builds ML/AI models using common methods within R and Python
• Analyzes the ML algorithms that could be used to solve a given problem and rank them by their success probability
• Analyzes errors of the model and design strategies to overcome errors
• Develop logging, alerting, and mitigation strategies for handling model errors
• Development of AI/ML models to distinguish relevant content or events and recognize patterns
• Designs and develops AI/ML models to predict member outcomes or future impact of key member decisions
• Evaluate and design experiments to monitor key model metrics and identify improvement opportunities
• Participate in presentations and communicate results of research analysis and findings to non-technical business partners
• Produces fairness review for each developed model, to ensure model is free of bias
• Set up continuous integration/continuous deployment (CI/CD) pipelines used for model automation
• Model deployment with containers such as Kubernetes and/or Docker
• Produce clean & readable code that has been properly unit tested and optimized for performance
• Completes proper deployment integration testing to ensure seamless deployment
• Maintains and supports AI/ML patterns by reviewing and solving issues and running ML/AI models
• Assists in leading team-wide initiatives that help develop templates and define best practices to improve model building and deployment workflow (ex. Model drift detection)
• Complies with all policies and standards
• Experience with SQL (Programming Language)
• Experience with Machine Learning; Machine Learning Algorithms; Statistics
• Knowledge of Python (Programming Language); R (Programming Language)
• Experience with Continuous Integration; Software Engineering

Benefits

• Health insurance
• 401K and stock purchase plans
• Tuition reimbursement
• Paid time off plus holidays
• A flexible approach to work with remote, hybrid, field or office work schedules
• Benefits may be subject to program eligibility.

Company Overview

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