Machine Learning Engineers II

Centene Corporation•Clayton, MO

7d•Remote

About The Position

You could be the one who changes everything for our 28 million members by using technology to improve health outcomes around the world. As a diversified, national organization, Centene's technology professionals have access to competitive benefits including a fresh perspective on workplace flexibility.

Requirements

Bachelor’s degree in Information Science and Technology, Statistics, Mathematics, Engineering, Computer Science, or related, or equivalent experience acquired through accomplishments of applicable knowledge, duties, scope and skill reflective of the level of this position, and 2 years of relevant work experience.
Designing, developing, and conducting research around Machine Learning (ML) systems, moderately complex models, and schemes to apply to appropriate datasets for data modelling and statistical analysis.
Maintaining and supporting ML/AI software platforms by reviewing and solving moderately complex issues and running moderately complex ML/AI models.
Analyzing errors of the Financial, Fraud Waste & Abuse models and designing strategies to overcome errors.
Writing software code to enable and automate machine learning model training and deployment.

Responsibilities

Design, develop, and conduct research around Machine Learning (ML) systems, moderately complex models, and schemes to apply to appropriate datasets for data modeling and statistical analysis.
Identify differences in data distribution that could affect model performance in real-world situations.
Analyze use cases of ML algorithms and apply findings to enable business decisions by deriving insights through data visualization.
Maintain and support ML/AI software platforms by reviewing and solving moderately complex issues and running moderately complex ML/AI models.
Understand and communicate business objectives and develop moderately complex models that help to achieve them, along with metrics to track their progress.
Write software documentation and moderately complex software code to extract data from a variety of databases and data sources.
Manage available resources such as hardware, data, and personnel so that deadlines are met and deploy predictive models using established software patterns.
Analyze the ML algorithms that could be used to solve a given problem and rank them by their success probability.
Explore and visualize data to gain an understanding of it and verify data quality, and/or ensure data quality via data cleaning.
Analyze errors of the model and design strategies to overcome errors.
Write software code to enable and automate machine learning model training and deployment.