Senior Data Scientist

Adonis•New York, NY

1d•Onsite

About The Position

Adonis is adding a new Senior Data Scientist to join our growing DS/ML team. You'll work across the modeling lifecycle, from exploratory analysis to production on real claims data, with clear ownership of your work and direct exposure to product and engineering. This role is ideal for someone who executes well independently and is ready to take on larger problem scopes. Adonis is the leading AI orchestration platform for healthcare revenue cycle management (RCM), purpose-built for healthcare organizations seeking to transform their revenue operations. Traditional RCM processes often struggle with inefficiencies, costing providers up to 15% or more of their potential revenue. Through advanced automation, data science, and AI Agents, Adonis helps revenue teams detect vulnerabilities, optimize workflows, and deploy precise solutions that drive reliable and scalable financial outcomes. Adonis is headquartered in New York City and has raised over $95M in funding, including a recent $40M Series C round led by Quadrille Capital with continued support from existing investors such as General Catalyst and Bling Capital. This funding supports our mission to restore sanity to RCM and equip provider groups and health systems with AI-driven revenue cycle operations at scale.

Requirements

Four plus years of experience in a data science or applied ML role
Demonstrated track record of taking models from development to production in a real product environment
Strong proficiency in Python and SQL
Experience taking at least one model from development to production
Solid grounding in statistics, probability, and ML fundamentals
Hands-on experience with ML frameworks : scikit-learn, XGBoost, or similar
Experience with cloud infrastructure, preferably AWS
Experience with data pipeline tooling and orchestration (sqlMesh, Temporal, or equivalent)
Ability to communicate findings clearly to both technical and non-technical audiences
Experience with MLOps tooling; experiment tracking (MLflow or similar), orchestration (Temporal, Prefect), and model monitoring

Nice To Haves

Exposure to EHR or RCM data specifically
Familiarity with anomaly detection methods
Familiarity with recommendation systems

Responsibilities

Build and deploy machine learning models that power our core analytics and intelligence features
Conduct exploratory data analysis on large-scale claims datasets to identify patterns and anomalies
Collaborate with engineering to integrate models and data products into production systems
Monitor model performance and iterate based on results
Communicate findings clearly to cross-functional stakeholders including product and customer-facing teams
Contribute to data pipeline and warehouse development as needed