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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** FRACTAL LLC - **Location:** United States - **Experience:** Expert - **Salary:** $140,000.0 - $150,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Microsoft Azure, Information Engineering, UN Electronic Data Interchange for Administration Commerce and Transport, Python (Programming Language), Machine Learning, NumPy, Rapid Prototyping Process, Recommender Systems, Tensorflow, Standard Sql, Azure Machine Learning, Azure Data Lake, Software Deployment, Cloud Platform System, Feature Engineering, Azure Data Factory, GitHub Copilot, Office365, Large Language Models, Prompt Engineering, Deep Learning, Generative AI, Pandas, Containerization, Data Lakes, Scikit Learn, Information Technology, Machine Learning Operations, Software Version Control, Databricks - **Published:** September 21, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/m3fse8pajw ## About the Role * Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Applied Mathematics, or a related quantitative field. * 8+ years of hands-on experience developing ML or AI models in an applied industry setting (healthcare experience strongly preferred).* Strong proficiency in: Databricks Python (pandas, scikit-learn, NumPy, TensorFlow, MLflow) SQL * Preferred: Knowledge of US healthcare, ideally with Revenue Cycle Management (RCM) experience, including familiarity with EDI transactions such as 837 and 835. * Ability to thrive in a fast-paced environment with rapid prototyping, ambiguity, and iterative delivery. * Required: Strong working knowledge of GitHub Copilot (or equivalent enterprise-approved AI coding assistant) to accelerate development. * Self-motivated and solution-oriented; able to independently research, troubleshoot, and identify paths forward when facing technical or data challenges. * Experience working in Azure or similar cloud environments: Azure Databricks (MLflow, Delta Lake) Azure Machine Learning Azure Data Lake / Azure Data Factory (in partnership with Data Engineering) * Hands-on experience in at least one of the following: Classification, regression, time series, or recommendation systems Agentic AI / Large Language Models (LLMs) / RAG * Strong statistical modeling foundation and experience building production-quality ML systems.* Ability to communicate technical findings to nontechnical stakeholders clearly and effectively. Required AI Skills: All contractor resources are expected to demonstrate baseline proficiency in enterprise-approved AI tools as part of their day-to-day responsibilities. This includes, but is not limited to: Consistent Use: Maintain a minimum of 90% weekly usage of AI tools such as GitHub Copilot, Microsoft 365 Copilot, and other GenAI platforms approved by the enterprise. Applied Productivity: Leverage AI tools to enhance coding, documentation, data analysis, and decision-making workflows. ## Description Team is seeking a talented and mission driven Data Scientist to design, develop, and deploy AI and machine learning solutions that transform the Healthcare Revenue Cycle Management (RCM) process. In this role, you will partner closely with Operations, Product, Data Engineering, and Engineering teams to build predictive models, generative AI solutions, and intelligent automation that improve efficiency across claims processing, denials and appeals, clinical documentation, coding, customer service, and related workflows. You will work hands on with cloud-native technologies-primarily in Azure Machine Learning and Databricks-to bring models from concept to production. This position is ideal for someone who is self-motivated and self-driven, thinks innovatively about how to unlock value from RCM data, and consistently presents solutions rather than being blocked by challenges. You should be comfortable operating in a fast-paced environment with rapid prototyping and iterative delivery, and be willing to research and find answers independently rather than expecting step-by-step guidance. Responsibilities * Develop machine learning, deep learning, and generative AI models to support RCM use cases such as claim outcome prediction, denials classification, next best action recommendation, clinical appeal summarization, and workflow optimization. * Build end to end ML pipelines including feature engineering, model training, hyperparameter tuning, validation, and monitoring. * Research and apply advanced techniques in LLMs, embeddings, retrieval augmentation (RAG), prompt engineering, and document intelligence. * Translate operational and product requirements into measurable model objectives, data specifications, and evaluation frameworks. * Conduct exploratory data analysis (EDA) to understand data patterns, anomalies, and business insights. * Implement and follow best practices around MLOps, including model versioning, reproducibility, feature stores, and drift monitoring. * Partner with Data Engineers to ensure feature availability, data quality, and scalable ML/AI deployment within Azure Databricks and enterprise platforms. * Collaborate with cross-functional teams to communicate insights, present model results, and drive adoption of ML solutions. * Maintain awareness of emerging AI technologies and propose enhancements or new opportunities for Provider Engineering platforms. ## Related Videos - [Vectorize all the things! 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