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Data ScientistSavas Management Center LLC • Scottsdale, AZ, US
Data Scientist

Data Scientist

Savas Management Center LLC • Scottsdale, AZ, US
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  • [job_card.full_time]
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Job Description

Job Description

Job Title : Data Scientist (Healthcare AI, Mid-Level)

Location : Scottsdale, AZ , $80K to $130K, must be authorized to work in USA, no visa sponsorship available

Company Overview : Lifekind Health is a leading provider of transdisciplinary pain management patient care and is launching Savas Software AI-enabled next generation healthcare software. We combine clinical excellence with advanced machine learning, analytics engineering, LLM analysis, and intelligent automation to transform how care is delivered.

We are committed to providing exceptional patient care and dedicated to improving healthcare delivery through innovative technology. We are building the data and ML foundation that will power the future of personalized, proactive, and value-based healthcare.

Position Overview :

We are seeking a technically strong, impact-driven Data Scientist with experience building ML-based predictive products and advanced analytics (including LLM based) in real-world environments. In this role, you will work with diverse and complex healthcare datasets—EHR, scheduling, billing, claims, structured & unstructured clinical data—to design, train, and deploy machine learning models that directly influence patient care, operational performance, and clinical efficiency.

This is a high-ownership, hands-on role where you’ll help shape our intelligent data platform, build production-ready features, experiment with models, and collaborate with engineering teams to deploy AI products. If you enjoy solving messy, high-impact healthcare problems using AI, this role is for you.

Key Responsibilities

Machine Learning & Predictive Analytics

  • Develop and deploy AI / ML models that power key products such as :

Procedure Appropriateness

  • Patient no-show prediction
  • Appointment optimization
  • Clinical risk stratification
  • Patient adherence forecasting
  • Provider utilization and throughput prediction
  • Perform feature engineering using clinical, operational, and financial data.
  • Experiment with algorithms (tree-based models, GLMs, ensemble methods, NLP, deep learning where appropriate).
  • Evaluate models using rigorous statistical and ML performance metrics.
  • Collaborate with ML Engineering to productionize models on Azure

    • Data Analysis & Insights

  • Conduct exploratory data analysis (EDA) on EHR, scheduling, billing, and procedural data to uncover trends, biases, and quality issues.
  • Translate clinical guidelines and workflows into computable, data-driven logic.
  • Generate actionable insights that drive clinical and operational decision-making.

    • Data & Feature Pipelines

  • Transform raw healthcare data into modeling-ready datasets (structured + unstructured).
  • Implement data validation, quality checks, and scalable transformation logic.
  • Collaborate with Data Engineering to ensure high-quality, well-governed data pipelines.

    • LLMs, NLP & Unstructured Data (Nice-to-Have but Valuable)

  • Work with LLMs (Open AI, Anthropic Claude) to research and conceptualize recommendations
  • Apply basic NLP techniques to extract signal from clinical notes and operational text.
  • Explore entity extraction, rule-based labeling, embedding-based features, etc.

    • Visualizations & Storytelling

  • Create dashboards and data visualizations using Power BI or Python to communicate insights.
  • Present findings and recommendations to clinicians, operations leaders, and executives.

    • Technical Environment (Azure AI / ML & Analytics)

    You’ll work within a modern AI / ML and analytics stack, including :

  • LLMs : Open AI, Anthropic Claude
  • Core Languages : Python, SQL
  • Libraries & Frameworks : Scikit-learn, XGBoost, LightGBM, Pandas, NumPy, NLP libraries
  • Visualization : Power BI, Plotly, Matplotlib, Seaborn

    • Qualifications

  • 2 or more years of experience in data science, machine learning, or applied analytics.
  • Strong Python + advanced SQL skills for data manipulation, modeling, and EDA.
  • Experience developing and evaluating ML models in real-world environments.
  • Experience with healthcare datasets (EHR, claims, clinical notes, billing, scheduling) is a strong advantage.
  • Strong understanding of feature engineering, statistical methods, and model validation.
  • Ability to clearly communicate technical concepts to non-technical stakeholders.

    • Preferred Skills

  • Exposure to Prompt Engineering and working with LLMs (Open AI, Anthropic Claude)
  • Exposure to NLP for clinical text.
  • Experience with Azure Data Factory, Azure Functions, Azure Open AI
  • Experience deploying or operationalizing ML models (Azure ML ideal).
  • Master’s degree in Data Science, CS, Statistics, Biomedical Informatics, or related field.
  • Familiarity with HIPAA, PHI handling, and healthcare data governance.

    • What Success Looks Like

  • Production-ready ML models that drive measurable improvements in clinical operations.
  • High-quality datasets, features, and reproducible pipelines powering our AI platform.
  • Actionable insights that influence patient outcomes and reduce operational friction.
  • Ability to independently drive complex data projects end-to-end with minimal supervision.

    • What Sets Us Apart :

    Our team is mission-driven and united by a common purpose : healing humanity through a revolutionary transdisciplinary model. The model addresses the quadruple aim of healthcare : enhancing patient experience, improving patient health, reducing healthcare costs, and increasing employee satisfaction. We thrive on collaboration, and each member is a self-starter, empowered to unblock themselves and move forward with confidence. If you are passionate about impacting healthcare, enjoy taking initiative, and are comfortable with ambiguity, you’ll find a great fit with us.

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