> Markdown version of [/jobs/ext/1916290-data-scientist](https://www.wearedevelopers.com/jobs/ext/1916290-data-scientist). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** ADONIS INC. - **Location:** New York, NY, United States - **Experience:** Expert - **Salary:** $225,000.0 - $250,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Cloud Computing, Cyber Security, Data Files, Data Warehousing, Python (Programming Language), Machine Learning, Recommender Systems, Tensorflow, Standard Sql, Juniper, Build Management, Scikit Learn, Xgboost, Data Management, Machine Learning Operations, Data Pipelines - **Published:** August 4, 2026 - **Apply:** https://www.careerbuilder.com/job-details/senior-data-scientist-new-york-ny--d3d616ec-1b04-432a-8ce7-434a2f69a730 ## About the Role * Eight 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 Have * Exposure to EHR or RCM data specifically * Familiarity with anomaly detection methods * Familiarity with recommendation systems, Analysis Skills, Artificial Intelligence (AI), Artificial Intelligence (AI) Agents, Automation, Communication Skills, Compensation Management, Computer Security, Cross-Functional, Customer Relations, Data Analysis, Data Management, Data Modeling, Data Science, Data Sets, Data Warehousing, Dental Insurance, Funding, Health Insurance, Healthcare, Healthcare Providers, Juniper Networks M-Series, Machine Tool, Performance Analysis, Performance Modeling, Philosophy, Product Engineering, Production Systems, Revenue Management, Vision Plan ## Description 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., * 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 ## Related Videos - [TikTok's Privacy Innovation](https://www.wearedevelopers.com/videos/1036-tiktok-s-privacy-innovation) - [Introduction to TXT](https://www.wearedevelopers.com/videos/30-introduction-to-txt) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Explainable machine learning explained](https://www.wearedevelopers.com/videos/589-explainable-machine-learning-explained) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Implementing continuous delivery in a data processing pipeline](https://www.wearedevelopers.com/videos/73-implementing-continuous-delivery-in-a-data-processing-pipeline) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)