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
Company H1B Sponsorship