Key skills
Healthcare data analyticsStatistical analysisData miningData management softwareData visualization softwareSASRSPSSStataSQLSSRSSQL ServerMinitabTableauQuantitative analysisBiostatistical data analysisOpportunity analysesRisk adjustmentPredictive modelingProgram evaluation studiesProbabilityinferenceLongitudinal analysisMixed effect modelingLogistic regressionModel building techniquesAlgorithm designInteractive reportingData visualizationModelingDatabase systemsTrend analysisRoot cause analysisComputer networksNeural networksData structuresProgramming languagesLogic designMicrosoft ExcelMicrosoft PowerPointMicrosoft WordMicrosoft VisioAnalyticsData MiningStatistical Analysis
About this role
Inovalon is a technology company focused on transforming the healthcare ecosystem through data-driven solutions. They are seeking Senior Healthcare Data Analytics Specialists to determine project plans, analyze healthcare data, and develop clinical analytic products to support business decisions.
Responsibilities:
- Determine project plans, timelines, and/or technical objectives for statistical aspects of healthcare data analytic processes, applying valid statistical techniques and using information obtained from baselines or historical data to structure uncompromised and efficient analyses
- Use data analysis to support and improve business decisions and develop clinical healthcare data analytic products and services
- Determine the specific types of clinical or healthcare data required to answer specific questions or solve problems
- Evaluate and maintain healthcare databases comprised of data from a variety of sources, such as clinical and health data contained in electronic health records and publicly reported quality measurement and reimbursement data and adjusting and weighting the raw data
- Prepare data for processing
- Plan and design data integration strategies by evaluating clinical and healthcare data to determine any reliability or usability limitations and checking for inaccuracies
- Develop, execute and reconcile requirements for data mapping and data loading processes, develop intuitive designs, and build enterprise interactive dashboards with built in guided healthcare data analytics
- Evaluate data to ensure validity, applicability, efficiency, and accuracy
- Perform complex and detailed statistical analyses and modeling of clinical and operational data with clear, relevant outputs
- Analyze data using statistical analysis and visualization software (e.g. SAS, R, SPSS, Stata, SQL or Tableau) to apply statistical approaches such as opportunity analyses, risk adjustment and predictive modeling, program evaluation studies, probability and inference, longitudinal analysis, mixed effect modeling, logistic regression analyses, and model building techniques
- Perform trend analysis to identify and research anomalies and outliers in the data
- Identify problem areas related to healthcare quality, risk adjustment, and/or clinical performance and recommend solutions
- Write detailed analysis plans and descriptions of analyses and recommendations, including preparing data visualizations in the form of dashboards, charts, and/or graphs
- Prepare statistical data for inclusion in reports to senior management, state or federal regulatory agencies, accrediting agencies, and clients
Requirements:
- Three of Four Year Bachelor's degree in Computer Science, Management Information Systems, Statistics, Data Analytics, Information Technology Management, Commerce, or related field of study, or foreign equivalent plus at least 5 years progressively responsible experience in job offered or in any related analytics job titles
- 5 years of experience with healthcare data analytic processes
- 5 years of experience conducting statistical analyses and data mining using data management and visualization software (e.g. SAS, R, SPSS, Stata, SQL, SSRS, SQL Server, Minitab, and/or Tableau)
- Experience with analytical, quantitative, statistical, and biostatistical data analysis methodology and theory (e.g. opportunity analyses, risk adjustment and predictive modeling, program evaluation studies, probability and inference, longitudinal analysis, mixed effect modeling, logistic regression analyses, and model building techniques)
- Experience with algorithm design, interactive reporting, data visualization and modeling, database systems, trend and root cause analysis, computer and neural networks, data structures, programming languages, and logic design
- Experience with Microsoft technologies (including Excel, PowerPoint, Word, and Visio)