Machine Learning Engineer (Contract) - US Healthcare Domain

Engagement & Shift Details

• Role Type: Contract (3 Months Initial with a high possibility of extension).
• Location: 100% Remote.
• Shift Timings: UK Shift.
• Work Week: Monday to Friday (Saturday & Sunday off).
• Priority: Urgent requirement; Immediate / Early Joiners are highly preferred.
  
  

Job Overview

We are seeking a highly skilled and analytical Machine Learning Engineer with deep expertise in Predictive Analytics and the US Healthcare ecosystem for an urgent, 3-month contract engagement (with a high likelihood of extension). This is a fully remote position operating on a UK Shift schedule, offering a stable Monday-to-Friday work week with weekends off.

As an initial experimental engagement, you will be responsible for translating complex healthcare data into actionable intelligence. You will design, build, and deploy predictive models that analyze provider engagement, prescription patterns, and operational behaviors. If you have 5+ years of experience, strong Snowflake proficiency, and a solid understanding of US healthcare structures, this high-impact role is for you.

Key Responsibilities1. ML Model Development & Predictive Analytics

• Design, build, train, and deploy production-grade Machine Learning models optimized for predictive analytics.
• Develop advanced statistical and predictive frameworks to uncover deep business trends and insights.
• Proactively explore large, complex datasets to identify useful data patterns and predictive indicators beyond predefined use cases.

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• Healthcare Data Architecture & Analysis
• Analyze large-scale structured and unstructured healthcare datasets with a specific focus on prescription data and healthcare provider engagement.
• Leverage Snowflake extensively for data warehousing, querying, and optimizing machine learning feature stores.
• Incorporate domain-specific healthcare standards into data pipelines to ensure contextual accuracy.
• MLOps & Production Integration
• Ensure absolute model scalability, robust performance, and production readiness.
• Establish and maintain modern MLOps best practices for model tracking, deployment, and version control.
• Collaborate closely with cross-functional and offshore teams to seamlessly integrate ML models into active business workflows.
  
  

Job Requirements & QualificationsTechnical Skills (Must Have)

• Experience: Minimum 5+ years of hands-on experience in Machine Learning engineering and predictive modeling.
• Core Engineering: Proficient in Python and standard ML frameworks/libraries (e.g., scikit-learn, XGBoost, PyTorch, or TensorFlow).
• Data Platforms: Strong, extensive hands-on experience working with Snowflake.
• Analytics & MLOps: Proven expertise in advanced statistical analysis, predictive modeling, and production-level MLOps pipeline management.
  
  

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Mandatory Domain Expertise (Non-Negotiable)

• Healthcare Domain: Solid, proven experience within the US Healthcare ecosystem is strictly mandatory.
• Data Competency: In-depth understanding of NPI (National Provider Identifier) registries and US Healthcare Taxonomy.
• Analytic Focus: Prior experience specifically handling Provider and Prescription Data Analysis alongside Healthcare Provider Engagement Analytics.
  
  

Soft Skills & Logistics

• Communication: Exceptional communication and collaboration skills are required for efficient offshore team alignment.
• Autonomy: Proven ability to work independently, troubleshoot under tight timelines, and adapt within a fast-paced environment.
  
  

⚠️ Screening Note to Applicants: Profiles without demonstrable US Healthcare domain experience, NPI/Taxonomy familiarity, or Snowflake expertise will not be considered for this role. Ensure these elements are clearly outlined on your resume.

Skills: python engineering,snowflake data platform,predictive analytics & ml modeling,us healthcare domain (npi & taxonomy),mlops production pipelines