Harness the power of your healthcare data
Healthcare Statistical Data Scientist
Location
United States
Posted
3 days ago
Salary
0
Seniority
Mid Level
Job Description
Healthcare Statistical Data Scientist
SmartLight Analytics
Role Description We’re seeking a Machine Learning Data Scientist with deep expertise in healthcare claims data to design, build, and deploy advanced analytics and machine learning modeling solutions. In this role, you’ll transform complex administrative and clinical datasets into actionable insights that improve cost efficiency, care quality, and operational performance across the healthcare ecosystem. You’ll collaborate with data engineers, clinicians, and product teams to develop predictive models, optimize workflows, and support strategic decision‑making. This position is ideal for someone who thrives at the intersection of data science, healthcare operations, and modern machine learning. Key Responsibilities - Machine Learning & Advanced Analytics - Develop, train, and deploy ML models for use cases such as: - Claims cost prediction and utilization forecasting - Fraud, waste, and abuse detection - Risk adjustment and member stratification - Provider performance and network optimization - Apply modern ML techniques including gradient boosting, deep learning, NLP, and probabilistic modeling. - Capable of applying advanced predictive analytics to correlate disparate datasets and events and derive business value. - Build scalable pipelines for feature engineering, model training, validation, and monitoring. - Healthcare Claims Expertise - Analyze and interpret medical, pharmacy, and dental claims (CPT/HCPCS, ICD‑10, DRG, NDC). - Translate domain knowledge into meaningful features and model strategies. - Cross‑Functional Collaboration - Partner with clinicians, product managers, and business stakeholders to define problems and measure outcomes. - Communicate complex analytical findings in clear, actionable terms. Qualifications - Strong proficiency in Python and ML libraries (scikit‑learn, XGBoost, TensorFlow/PyTorch). - Hands-on experience with healthcare claims datasets and coding systems. - Solid understanding of statistical modeling, machine learning algorithms, and data mining techniques. - Strong knowledge and expertise working with SQL. - Ability to translate business needs into analytical solutions. - Must have demonstrated the ability to solve complex problems with minimal direction. Preferred Qualifications - Experience with NLP applied to clinical notes or unstructured healthcare data. - Familiarity with actuarial concepts, risk scoring, or value‑based care models. - Familiarity deploying models into production (MLOps, CI/CD). - Background in health economics, epidemiology, or biostatistics. - Prior work with FHIR, HL7, or interoperability standards. Company Description SmartLight Analytics was formed by a group of industry insiders who wanted to make a meaningful impact on the rising cost of healthcare. With this end in mind, SmartLight combats fraud, waste, and abuse in healthcare through our proprietary data analysis and model development. Requiring the bare minimum in employer involvement, our process works behind the scenes to save money without interrupting employee benefits or requiring employee behavior changes.
Related Guides
Related Categories
Related Job Pages
More Data Scientist Jobs
• develop and implement sales strategies that align Presidio and OEM solutions with client needs • understand customer priorities and technology requirements, act as a trusted advisor, and consistently achieve revenue and performance targets • strengthen Presidio’s presence in key accounts through strategic engagement while promoting company values and collaborating across teams to enhance overall sales strategy • monitor technology trends and competitive developments to position Presidio effectively • collaborate with solution architects to identify client infrastructure challenges, define requirements, and deliver tailored modernization strategies that showcase Presidio’s differentiators • build strong relationships with OEM executives, channel leaders, and account teams • provide thought leadership and represent Presidio at industry events to expand pipeline, increase brand awareness, and strengthen market presence • ensure consistent branding and unified go-to-market strategies with OEM partners • track competitive activity and gather insights on pricing, products, and delivery strategies
• Oversee the design, development, and maintenance of data infrastructure and architecture for Oil, Gas, and Remediation projects. • Drive data generation, storage, processing, and warehousing initiatives. • Ensure the implementation of effective data management solutions and best practices. • Develop, construct, test, and maintain databases and large-scale data processing systems. • Ensure data is accessible, reliable, secure, and efficiently processed. • Combine, optimize, and manage multiple large-scale data sources. • Create automated reporting systems and data solutions. • Provide software solutions that move data from its source to internal databases, including data warehouses. • Implement and maintain data frameworks and architectures. • Develop and maintain data pipelines to support data analysis, reporting, and business intelligence. • Analyze complex issues and recommend solutions that improve data warehousing processes and methodologies. • Use judgment outside defined parameters and precedents to make decisions and resolve business and technical challenges. • Be accountable for the results of assigned projects and processes. • Demonstrate strong proficiency in data programming languages. • Demonstrate strong knowledge of data optimization tools, data structures, data architecture, and data warehousing solutions. • Demonstrate strong knowledge of API (Application Programming Interface) integration to support data access, collection, distribution, transformation, and ELT (Extract, Load, Transform) processes. • Apply algorithmic and statistical methods, data processing tools, and AI-enabled approaches to support efficient data consumption and analysis.
• Oversee the design, development, and maintenance of data infrastructure and architecture for Oil, Gas, and Remediation projects • Drive data generation, storage, processing, and warehousing initiatives while ensuring the implementation of effective data management solutions and best practices • Develop, construct, test, and maintain databases and large-scale data processing systems • Ensure data is accessible, reliable, secure, and efficiently processed • Combine, optimize, and manage multiple large-scale data sources • Create automated reporting systems and data solutions • Provide software solutions that move data from its source to internal databases, including data warehouses • Implement and maintain data frameworks and architectures • Develop and maintain data pipelines to support data analysis, reporting, and business intelligence • Analyze complex issues and recommend solutions that improve data warehousing processes and methodologies
• Oversee the design, development, and maintenance of data infrastructure and architecture for Oil, Gas, and Remediation projects • Drive data generation, storage, processing, and warehousing initiatives while ensuring the implementation of effective data management solutions and best practices • Develop, construct, test, and maintain databases and large-scale data processing systems • Ensure data is accessible, reliable, secure, and efficiently processed • Combine, optimize, and manage multiple large-scale data sources • Create automated reporting systems and data solutions • Provide software solutions that move data from its source to internal databases, including data warehouses • Implement and maintain data frameworks and architectures • Develop and maintain data pipelines to support data analysis, reporting, and business intelligence • Analyze complex issues and recommend solutions that improve data warehousing processes and methodologies • Use judgment outside defined parameters and precedents to make decisions and resolve business and technical challenges • Accountable for the results of assigned projects and processes • Demonstrate strong proficiency in data programming languages and knowledge of data optimization tools, data structures, data architecture, and data warehousing solutions • Knowledge of API (Application Programming Interface) integration to support data access, collection, distribution, transformation, and ELT (Extract, Load, Transform) processes • Apply algorithmic and statistical methods, data processing tools, and AI-enabled approaches to support efficient data consumption and analysis.
