Operations Analytics Data Scientist

RadNet

2d • $95,000 - $150,000

About The Position

Artificial Intelligence; Advanced Technology; The very best in patient care. With decades of expertise, RadNet is Leading Radiology Forward. With dynamic cross-training and advancement opportunities in a team-focused environment, the core of RadNet’s success is its people with the commitment to a better healthcare experience. When you join RadNet as an Operation Analytics Data Scientist, you will be joining a dedicated team of professionals who deliver quality, value, and access in the 21st century and align all stakeholders- patients, providers, payors, and regulators to achieve the best clinical outcomes.

Requirements

• Master’s or Ph.D. in Data Science, Statistics, Computer Science, Mathematics, or related quantitative field; or Bachelor’s with equivalent experience
• 3+ years of experience in data science, machine learning, or advanced analytics roles
• Strong proficiency in Python and data science libraries (pandas, NumPy, scikit-learn, statsmodels)
• Experience with machine learning frameworks (PyTorch, TensorFlow, XGBoost, LightGBM)
• Solid foundation in statistics including regression, hypothesis testing, experimental design, and time series analysis
• Proficiency in SQL for data extraction and manipulation
• Experience with data visualization tools (Matplotlib, Seaborn, Plotly, or BI tools)
• Excellent communication skills with ability to explain complex analyses to non-technical stakeholders

Nice To Haves

• Experience with cloud ML platforms (GCP Vertex AI, AWS SageMaker, Azure ML)
• Knowledge of MLOps practices and model deployment pipelines
• Healthcare analytics experience including clinical, operational, or revenue cycle domains
• Experience with causal inference, Bayesian methods, or optimization techniques
• Familiarity with LLMs, NLP, or generative AI applications
• Experience with big data technologies (Spark, BigQuery, Databricks)
• Track record of deploying models that delivered measurable business impact

Responsibilities

• Predictive & Prescriptive Analytics
• Develop analytical models that drive business outcomes:
• Design and build predictive models for forecasting, demand planning, and capacity optimization
• Develop risk and anomaly detection systems for operational and clinical metrics
• Create scenario analysis and "what-if" models to support strategic decision-making
• Build decision-scoring frameworks that quantify trade-offs and recommend actions
• Translate business problems into analytical frameworks with measurable outcomes
• Machine Learning & Model Development
• Build, validate, and deploy ML models as enterprise assets:
• Develop feature engineering pipelines using governed data from the Gold Layer
• Train, validate, and evaluate machine learning models using appropriate techniques and frameworks
• Implement model monitoring for drift, bias, and performance degradation
• Create model documentation including methodology, assumptions, limitations, and explainability
• Partner with AI Engineers to deploy models into production environments
• Statistical Analysis & Research
• Apply rigorous analytical methods to answer business questions:
• Conduct exploratory data analysis to identify patterns, trends, and insights
• Apply statistical methods (regression, hypothesis testing, time series analysis) to validate findings
• Design and analyze experiments (A/B tests, randomized trials) to measure intervention impacts
• Quantify uncertainty and communicate confidence levels in analytical outputs
• Stay current with advances in data science, ML, and AI methodologies
• AI Measurement & Effectiveness
• Measure and optimize the impact of AI initiatives
• Define metrics and KPIs to measure AI model effectiveness and business impact
• Track and report on model performance in production environments
• Evaluate AI outputs for accuracy, bias, and fitness for purpose
• Provide feedback to improve AI systems based on real-world performance
• Support responsible AI practices including fairness testing and transparency
• Stakeholder Collaboration & Communication
• Partner with business teams to deliver analytical value
• Collaborate with business stakeholders to understand problems and translate them into analytical projects
• Present findings and recommendations to technical and non-technical audiences
• Create visualizations and narratives that make complex analyses accessible and actionable
• Partner with BI teams to operationalize analytical insights into dashboards and reports
• Coach and mentor analysts on statistical thinking and advanced analytical techniques

Benefits

• Comprehensive Medical, Dental and Vision coverages.
• Health Savings Accounts with employer funding.
• Wellness dollars
• 401(k) Employer Match
• Free services at any of our imaging centers for you and your immediate family.
• Pay Range: $95,000.00 – $150,000.00 per year

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level