Senior Data Scientist

Requirements

• Masters Degree in Mathematics, Statistics, Engineering, Computer Science, Data Sciences, Social Sciences, Business Analytics, or related field
• 2 years experience in a position requiring use of technical software such as SQL, IBM SPSS, Tableau or Python in developing data models, reporting and analytical processes to support program requirements and stakeholders
• Experience using statistical and data mining techniques
• Experience developing processes and tools to monitor and analyze model performance and data accuracy
• Experience using statistical tools such as SAS, IBM SPSS
• Data Visualization/presentation skills

Qualifications

• Experience using Tableau

Skills

• Use of technical software such as SQL, IBM SPSS, Tableau or Python in developing data models, reporting and analytical processes to support program requirements and stakeholders
• Statistical and data mining techniques
• Developing processes and tools to monitor and analyze model performance and data accuracy
• Using statistical tools such as SAS, IBM SPSS
• Data Visualization/presentation skills

Responsibilities

• Turn data into critical information/knowledge that can be used to make sound organizational decisions for healthcare organization
• Mentor Data Scientists and other staff in the development of process improvement and evaluation opportunities to increase the efficiency of the reporting process
• Combine seemingly unrelated data concepts to identify trends and to solve complex problems
• Design experiments and tests hypotheses to support quality and/or financial performance improvement initiatives
• Evaluate options to complex problems by using mathematics and statistical methods
• Lead process discovery sessions to define operation definitions for data and identify stakeholders requirements for work in an ambiguous, constantly changing environment
• Integrate and prepare large, varied datasets, architect specialized databases and computing environments from disparate data sources, and specifically with Epic
• Investigate program requirements as they are rolled out, determine optimal data sources and processes to stand up analytics to support these programs
• Develop and propose innovative ways to look at problems by using data mining approaches on the set of information available
• Validate findings using an experimental and iterative approach
• Present analyses and/or findings to the business and validate the work in a way that can be easily understood by business stakeholders
• Develop processes and tools to monitor and analyze model performance and data accuracy