Develop and deploy machine learning models for anomaly detection, focusing on structured and unstructured data to identify fraud patterns.
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, permanent/full-time Machine Learning Engineer to join our team. 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 Responsibilities
- Design and implement ML-based anomaly detection algorithms.
- Process and analyze unstructured marketing data from social media advertising platforms.
- Develop NLP pipelines for analyzing ad content and detecting deceptive marketing claims.
- Create and refine detection algorithms that combine multiple data signals.
- Implement feature engineering processes for time-series and behavioral data.
- Establish model monitoring and performance tracking systems.
- Collaborate with Business Analyst on rule-based detection criteria.
- Implement feedback loops for continuous model improvement.
Minimal Requirements
- Master's degree in Data Science, Statistics, Machine Learning, or related field.
- 4+ years of experience in machine learning and data science.
- Expert proficiency in Python and ML frameworks (scikit-learn, TensorFlow, PyTorch).
- Strong background in anomaly detection and time-series analysis.
- Experience with NLP and text processing techniques.
- Knowledge of feature engineering and model deployment best practices.
- Experience with AWS ML services (SageMaker, Comprehend).
- Understanding of model governance and MLOps practices.
- US Citizenship or Permanent Residency required.
- Must reside in the Continental US.
- Depending on the government agency, specific requirements may include public trust background check or security clearance.
Preferred Qualifications
- Experience with using anomaly detection techniques for fraud detection.
- Knowledge of unsupervised learning techniques.
- Experience with real-time model serving and inference.
- Experience using graph databases.
Location
Be in your Element residing anywhere in the Continental US. We are a remote-first company based in Washington, DC.
Element is an Equal Opportunity Employer all 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.
Top Skills
Aws Ml Services
Python
PyTorch
Scikit-Learn
TensorFlow
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