Senior Data Science / ML Engineer
Department: Engineering
Location: United States
Employment Type: FullTime
About Anomaly
Founded in 2020, Anomaly uses AI and healthcare transaction data to decode complex payer behavior and close the knowledge gap between providers and payers. Our AI engine, Smart Response, analyzes hundreds of millions of healthcare encounters in real time to detect shifting payer rules and denial patterns. By continuously adapting to payer logic, it helps providers predict denials, reverse revenue loss, and hold payers accountable.
Our Products and Stack
Anomaly builds a suite of machine learning and analytics products designed to uncover health insurance company payment patterns. Our products include:
Detect - a web front-end product to surface newly discovered insurance payment patterns and behavior changes utilizing time-series analyses.
Predict - high-throughput API for machine-learning-powered claim denial prediction with configuration and monitoring live in the web front-end.
Recover - an analytics-driven product to prioritize denied accounts in order to assist our clients in denial recovery using algorithmic ranking and recommended actions that are fine-tuned towards high-dollar denial reversals.
About the Role
As a Senior Data Science / ML Engineer, you will drive the full data pipeline - from ingesting raw client data in multiple formats to producing refined datasets and models used across the Anomaly product suite. You’ll collaborate closely with product managers, data scientists, and senior executives to clarify objectives and rapidly iterate through innovative analytics experiments, paving the way for impactful client solutions.
Key Responsibilities:
Develop and maintain scalable data pipelines for diverse client datasets
Collaborate cross-functionally to translate complex problems into data-driven solutions
Design, implement, and optimize machine learning models for product integration
Rapidly prototype and iterate on novel analytics approaches with a focus on real-world impact
Participate in the end-to-end product development lifecycle, from conception through integration
Required Experience
5+ years in a dynamic, fast-paced team environment
Strong computer science fundamentals
Expert-level proficiency of SQL and Python
Deep experience with data science and machine learning libraries and techniques in Python
Familiarity with healthcare claim structures and coding systems (CPT, HCPCS, ICD-10)
Experience on a data science team where iterative experimentation drives innovation
Required Traits
Ability to iterate quickly and seek feedback when confronted with ambiguous requirements
A love of solving tricky technical and business problems with great teammates
Capable of owning the analytics product development process end-to-end, from prototype to production
Nice to have
Familiarity with PySpark and working in a Databricks environment.
Experience with EHR records, including structured data as well as unstructured clinical notes
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