Senior Data Scientist

Adonis•New York, NY

1d•$190,000 - $210,000

About The Position

Adonis is hiring a Senior Data Scientist to join its growing data science and machine learning team. The role spans the modeling lifecycle, from exploratory analysis through production, using real claims data. The successful candidate will own work independently, take on larger problem scopes, and work directly with product and engineering. The position focuses on building and deploying machine learning models for Adonis’s analytics and intelligence features, analyzing large-scale claims datasets, integrating models and data products into production, monitoring and improving model performance, and communicating findings to cross-functional stakeholders. The role may also contribute to data pipeline and warehouse development. Adonis is an AI orchestration platform for healthcare revenue cycle management. The company is headquartered in New York City. The listed base salary range is $190,000–$210,000, with compensation depending on job-related knowledge, skills, and experience. The company also offers equity and benefits.

Requirements

At least four years of experience in a data science or applied machine learning 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 machine learning fundamentals.
Hands-on experience with machine learning frameworks such as scikit-learn, XGBoost, or similar.
Experience with cloud infrastructure, preferably AWS.
Experience with data pipeline tooling and orchestration, such as sqlMesh, Temporal, or equivalent.
Ability to communicate findings clearly to technical and non-technical audiences.
Experience with MLOps tooling, including experiment tracking (MLflow or similar), orchestration (Temporal, Prefect), and model monitoring.

Nice To Haves

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

Responsibilities

Build and deploy machine learning models that power 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.