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A leading company is seeking an experienced Machine Learning Engineer for a temporary 12-month project in Washington, DC. The role focuses on developing and deploying ML models to prevent fraud in healthcare, emphasizing the ability to process various data types. Candidates should possess a Master's degree and extensive experience in machine learning tools and practices.
Who is Element?
We serve as a partner at the intersection of innovation and our clients' needs, efficiently crafting meaningful user experiences for government and commercial customers. By breaking down complex problems to their fundamental elements, we create modern digital solutions that drive efficiencies, maximize taxpayer dollars, and deliver essential outcomes that serve the people.
Why Work at Element?
Make an impact that resonates-join our vibrant team and discover how you can improve lives through digital transformation. Our talented professionals bring unparalleled energy engagement, setting a higher standard for impactful work. Come be a part of our team and shape a better future.
Position Overview
We are looking for an experienced Machine Learning Engineer to join our team on a temporary, 12 month project. As a Machine Learning Engineer, you will develop and deploy machine learning models for anomaly detection, processing both structured data and unstructured marketing content to identify suspicious behavior patterns and anomalous activities. As a member of this project, you will help ensure the delivery of healthcare to millions of Americans by monitoring and preventing fraud, waste, and abuse.
Key ResponsibilitiesLocation
Be in your Element. We are a remote-first company based in Washington, DC.
Element is an Equal Opportunity Employerall qualified applicants will receive consideration for employment without regard to age, ancestry, race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status, marital status, protected veteran status, or any other legally protected class.
We believe in a world where solutions we build improve the lives of those who use them.