Machine Learning Specialist

TAO Digital Solutions; United States; On-site; USD 90,000 - 120,000; Full time

Job summary

A leading healthcare technology management company is seeking a professional to join a small, high-impact team focused on advanced analytics and machine learning initiatives. Responsibilities include developing statistical models, performing financial analyses, and designing data pipelines for healthcare datasets. The ideal candidate holds a Master’s or Ph.D. and has over three years of experience in ML model deployment. This position involves collaboration across teams and ensuring compliance with healthcare data standards.

Qualifications

• Master’s or Ph.D. in Statistics, Economics, Data Science or related field.
• 3+ years of experience in ML model development and deployment.
• Strong foundation in statistical inference, econometrics, and causal analysis.
• Proficiency in Python, SQL, and ML frameworks.
• Excellent communication skills for presenting insights.

Responsibilities

• Develop and deploy statistical and machine learning models for maintenance and efficiency.
• Perform econometric and financial analysis for capital planning.
• Design data pipelines for large-scale healthcare datasets.
• Collaborate with cross-functional teams for actionable strategies.
• Ensure compliance with HIPAA and data governance standards.

Skills

ML model development and deployment

Statistical inference

Econometrics

Causal analysis

Python

SQL

Communication skills

Education

Master’s or Ph.D. in Statistics, Economics, Data Science

Tools

Scikit-Learn

XGBoost

TensorFlow

AWS

Azure

Job description

We are building a small, high-impact team to support advanced analytics and machine learning initiatives for a leading healthcare technology management company. This team will focus on predictive modeling, cost optimization, and ROI analysis for clinical asset management and capital planning.

Key Responsibilities

• Develop and deploy statistical and machine learning models for predictive maintenance, resource optimization, and operational efficiency.
• Perform econometric and financial analysis to support capital planning and cost-benefit decisions.
• Design and implement data pipelines for large-scale healthcare datasets (EHR, claims, RTLS, device telemetry).
• Collaborate with cross-functional teams (clinical engineering, finance, IT) to translate insights into actionable strategies.
• Ensure compliance with HIPAA and healthcare data governance standards.

Required Qualifications

• Master’s or Ph.D. in Statistics, Economics, Data Science, or related field.
• 3+ years of experience in ML model development and deployment.
• Strong foundation in statistical inference, econometrics, and causal analysis (e.g., regression, Bayesian methods, DiD).
• Proficiency in Python, SQL, and ML frameworks (Scikit-Learn, XGBoost, TensorFlow).
• Excellent communication skills for presenting insights to technical and business stakeholders.

Preferred Skills

• Experience with healthcare data (EHR, claims, RTLS).
• Familiarity with capital planning and ROI modeling.
• Knowledge of cloud platforms (AWS, Azure) and containerized deployments.