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Quest Analytics, LLC
Quest Analytics, LLC
51 – 200 Employees
ConsultingHealthcareLogistics

Quest Analytics, LLC develops network management software and services for healthcare provider networks. Its cloud-based Quest Enterprise Services and Quest Analytics Suite help health systems, regulators, and payers manage provider data, assess network performance, support compliance, and evaluate network adequacy.

Founded in 1993, the company combines healthcare analytics and consulting expertise to improve the accuracy, efficiency, and accessibility of provider-network information across the United States. Its work supports organizations seeking to strengthen healthcare access and maintain reliable, high-quality provider networks.

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Senior Healthcare Data Scientist (Hybrid, United States)

Develop production machine learning and AI solutions for healthcare provider network products. Improve provider-data quality, analytics, and network intelligence through advanced modeling and scalable data systems.

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Description

  • Build, optimize, and scale machine learning models and advanced analytics for provider-data quality and network intelligence
  • Use statistical modeling, predictive analytics, and machine learning to address business challenges
  • Investigate healthcare and provider-data problems, develop hypotheses, and define analytical approaches
  • Create original algorithms for complex analytical problems
  • Assess and improve model accuracy, performance, scalability, reliability, and business value
  • Process and analyze large datasets with Python, SQL, Databricks, Spark, and distributed computing technologies
  • Build and maintain automated workflows for anomaly detection, data validation, feature engineering, and ongoing model monitoring
  • Define feature engineering approaches and assess model effectiveness
  • Assess and integrate external data sources, tools, and vendors
  • Work with Engineering to deploy models and create scalable software solutions
  • Use LLM tools such as Claude while investigating generative AI, NLP, and AI-agent applications
  • Create measures for model performance, data quality, and business outcomes
  • Turn complex analytical results into practical recommendations
  • Share findings and recommendations with leadership and broader company audiences
  • Collaborate with Product and business teams on features, metrics, and data-informed solutions
  • Coach data scientists and analysts while advancing technical standards, data governance, and MLOps practices
  • Contribute to cross-functional programs and analytics discussions with clients

Requirements

  • At least seven years of experience in data science, machine learning, or advanced analytics, preferably within a SaaS organization
  • A master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field, or equivalent relevant experience
  • Proven ability to build and deploy machine learning models in production
  • Advanced Python proficiency, including pandas, NumPy, and scikit-learn
  • Strong experience with Databricks, Spark, or similar distributed computing platforms
  • Advanced SQL proficiency
  • Experience with TensorFlow, PyTorch, or comparable machine learning frameworks
  • Strong knowledge of classification, regression, clustering, NLP, and anomaly detection
  • Applied statistics expertise covering hypothesis testing, regression analysis, and probability
  • Experience handling large, untidy, and complex datasets
  • Working knowledge of MLOps practices, including deployment, monitoring, validation, and model lifecycle management
  • Experience applying LLMs and AI-assisted tools to data science workflows
  • Ability to independently navigate ambiguous problems and establish an effective course of action
  • Ability to communicate complex technical results in terms of clear business value
  • Strong cross-functional collaboration skills across Product, Engineering, Data, and business stakeholders
  • Experience directing technical initiatives and mentoring colleagues
  • Legal authorization to work in the United States
  • Visa sponsorship is not currently available
  • Preferred work locations are in one of the listed United States states

Benefits

  • Choice of remote, hybrid, or office-based work arrangements
  • Employee medical, dental, and vision plans with low employee costs
  • 401(k) matching
  • Wellness programs
  • Competitive pay and a success-sharing bonus
  • Flexible vacation, sick leave, and paid holidays
  • Entrepreneurial work culture
  • Recognition and rewards for contributions
  • Virtual interviews with cameras enabled
  • Equal employment opportunity and disability accommodations

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