Informatics Data Scientist
Informatics Data Scientist
Under the general direction of the Assistant Informatics Section Chief, applies sophisticated mathematical methods to integrate public health data and improve accuracy and completeness of information related to healthcare quality and interprets the data to promote health outcomes. Uses machine learning and data modeling to create algorithms and predictive models to support data analysis. Performs complex statistical analysis to validate data trends. Serves as subject matter expert for predictive analytics, statistics, and data modeling. Communicates public health data to a range of audiences.
- Uses machine learning and large-scale data modeling to create algorithms and predictive models to support data analysis. Creates, experiments and prototypes new learning algorithms and prediction techniques. Develops improvements to previously developed algorithms. Implements algorithms and statistical models for machine learning. Verifies model and algorithm effectiveness based on real world results. Tests and develops programming modifications. Writes, tests, and implements programs using software such as SAS, Stata, R, or Python to clean, manage, merge, and analyze large public datasets. Reviews applications, data sets, and models for anomalies to ensure accuracy. Captures user identity administration exceptions and determines and documents course of action for resolution.
- Performs complex statistical analysis to validate data trends. Manages and merges data from multiple sources and generates reports. Performs validation and quality assurance processes for measurement and analytical products.
- Serves as subject matter expert for predictive analytics, statistics and data modeling. Engages with IDPH data stewards and external stakeholders to understand data needs. Identifies and recommends areas for data alignment and linkages. Recommends and applies solutions related to data mining and predictive analytics.
- Communicates public health data to a range of audiences. Organizes and writes technical reports to communicate healthcare quality and population health information. Presents complex data science processes and analysis to non-technical audiences as action-oriented recommendations.
- Requires knowledge, skill and mental development equivalent to completion of four years of college in statistics, information management science, computer science, computer engineering, electrical engineering, physics, or a closely related field.
- Requires at least four years of experience in developing predictive and probabilistic linking models and algorithms.
- Requires at least five years of experience in data modeling including developing algorithms for data processing, pattern recognition, statistics, biostatistics, predictive and prescriptive modeling.
- Progressive experience in designing, customizing, and integrating machine learning and predictive algorithms.
- Proven ability to write clear and concise analytical documentation, summaries of various methodologies, and descriptions of statistical results, as well as create charts, tables, and other visual aids.
- Demonstrated experience in troubleshooting and managing issues related to identities.
- Proficiency with a programming language such as SAS, Stata, R, Python.
- Expert SQL user and experience with Business Intelligence tools such as Tableau. Experience with IBM data science platform is a plus.
- Requires excellent written and verbal communication skills.
Requires strong interpersonal and communication skills to collaborate effectively with team and multiple stakeholders