Data Science/ML Engineer

Data Science/ML Engineer

Posted 7 days ago by 1753426812

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Negotiable
Outside
Remote
USA
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Agile Methodology Azure Databricks Cloud Computing Cloud Technology Computer Science Databricks Data Infrastructure Data Preprocessing Data Science Feature Engineering Income / Revenue Machine Learning Microsoft Azure Predictive Modeling Python (Programming Language) PyTorch (Machine Learning Library) Scikit-learn (Machine Learning Library) SQL (Programming Language) Stakeholder Management TensorFlow Xgboost

Summary: We are looking for a Senior Machine Learning Engineer to join the Foundational Data Analytics Program, focusing on creating a modern data ecosystem. The role involves leading the design, development, and deployment of machine learning models to enhance enterprise analytics and healthcare transformation. The engineer will work with diverse data sources and collaborate with various stakeholders to drive predictive insights. This position emphasizes model interpretability and compliance with healthcare regulations.

Key Responsibilities:

  • Design and implement scalable machine learning pipelines using structured and unstructured healthcare data.
  • Collaborate with data engineers, architects, and business stakeholders to identify opportunities for predictive modeling and advanced analytics.
  • Develop and deploy models for risk stratification, member engagement, cost prediction, and quality improvement.
  • Ensure model interpretability, fairness, and compliance with healthcare regulations (e.g., HIPAA).
  • Monitor model performance and retrain as needed to maintain accuracy and relevance.
  • Contribute to the development of reusable ML components and frameworks within the FDA platform.
  • Mentor junior ML engineers and data scientists.

Key Skills:

  • Bachelor's or master's degree in computer science, Data Science, or related field.
  • 8+ years of experience in machine learning engineering or applied data science.
  • Proficiency in Python, SQL, and ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch.
  • Experience with cloud platforms (Azure preferred) and tools like Databricks, MLflow, or Azure ML Studio.
  • Strong understanding of data preprocessing, feature engineering, and model evaluation.
  • Familiarity with healthcare data standards (FHIR, HL7) and payer systems.
  • Excellent communication and collaboration skills.

Salary (Rate): undetermined

City: undetermined

Country: USA

Working Arrangements: remote

IR35 Status: outside IR35

Seniority Level: Senior

Industry: IT

Detailed Description From Employer:

We are seeking a highly skilled Senior Machine Learning Engineer to join the Foundational Data Analytics (FDA) Program, a strategic initiative focused on building a modern, intelligent data ecosystem. This role will lead the design, development, and deployment of machine learning models that support enterprise-wide analytics, predictive insights, and healthcare transformation.

FDA Program Objectives:

  • Single Source of Truth (SSOT): Build standardized, high-quality data infrastructure ensuring consistency and reliability.
  • Multifunctional Version of Truth (MVOT): Enable agile integration of diverse data sources for dynamic analytics.
  • Centralized Business Intelligence: Deliver automated, real-time insights to optimize cost, quality, and performance.
  • Capability Building: Strengthen population health, member engagement, quality improvement, revenue optimization, total cost of care, and compliance/risk functions.

Key Responsibilities:

  • Design and implement scalable machine learning pipelines using structured and unstructured healthcare data.
  • Collaborate with data engineers, architects, and business stakeholders to identify opportunities for predictive modeling and advanced analytics.
  • Develop and deploy models for risk stratification, member engagement, cost prediction, and quality improvement.
  • Ensure model interpretability, fairness, and compliance with healthcare regulations (e.g., HIPAA).
  • Monitor model performance and retrain as needed to maintain accuracy and relevance.
  • Contribute to the development of reusable ML components and frameworks within the FDA platform.
  • Mentor junior ML engineers and data scientists.

Required Skills & Qualifications:

  • Bachelor s or master s degree in computer science, Data Science, or related field.
  • 8+ years of experience in machine learning engineering or applied data science.
  • Proficiency in Python, SQL, and ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch.
  • Experience with cloud platforms (Azure preferred) and tools like Databricks, MLflow, or Azure ML Studio.
  • Strong understanding of data preprocessing, feature engineering, and model evaluation.
  • Familiarity with healthcare data standards (FHIR, HL7) and payer systems.
  • Excellent communication and collaboration skills.
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