The Data Scientist is responsible for performing advanced analytics in support of the Healthcare Analytics Solutions product portfolio. In this role, you will leverage your experience preparing large datasets and applying a variety of data science methods and the underlying mathematical theories to analyze data. The incumbent will work across our primary markets including, Pharma, Health Plans, and Health Systems and use the spectrum of data science fields of study, including natural language processing, machine learning and AI technology, to address the biggest challenges facing each market.
- Work with a cross-functional team of analysts, medical doctors, business leaders, and IT professionals to develop and deliver informatics and analytics services utilizing data from varied healthcare related data sources.
- Lead the development and streamlining of data processing algorithms that transform non-standard data into uniform structures required for robust analysis.
- Responsible for developing and maintaining clinical database for research and reporting purposes
- Write reports and develop presentation materials for communicating methodologies and findings to technical and business audiences.
- Participate as a Lead, Subject Matter Expert in enterprise projects that enable the use of data for analytics across Quest. This requires collaborating with business and technical teams to propose solutions and/or leverage new technologies to address data quality, normalization, and standardization issues.
- Leverage data visualization tools and software to present large amounts of information in charts, graphs, or other diagrams that are easy to interpret and spot patterns, trends, and correlations.
- Develop and maintain a clinical database for research and reporting purposes.
- Perform data studies and builds statistical models leveraging Quest and non-Quest data.
- Tests and validates predictive models.
- Effectively summarize results, in written report and presentation formats, from analysis to a diverse set of audiences with varying background and technical skills.
- Master’s degree preferred in quantitative field including Computer Science, Statistics or Biostats.
- Preferred experience building predictive analytics, machine learning, and statistical modeling
- 5+ years’ experience performing data analysis, preferably data mining, pattern recognition, statistical, and/or mathematical programming and modeling to health-related data.
- Advanced degree preferred in quantitative field including Computer Science, Math, Statistics or Biostats or other field related to data science or advanced analytics.
- Prefer 10+ years of professional SAS programming experience, prefer in healthcare industry
- Experience in working with very large and unstructured clinical data
- Knowledge and experience in developing analytics solutions in a cloud environment using modern data science tools, programming languages, and libraries
- Knowledge of the latest machine learning and data visualization tools and methods as applied in business contexts
- Experience with time series data leveraging methods such as regression, classification, survival analysis
- Prefer 5+ years of professional SAS programming experience, prefer in healthcare industry, experience in with SAS Viya is a plus
- Proficient in Unix Shell Script. SQL
- Experience with R, C++ and other programming language a plus
- Experience with Microsoft Office products and GIS tools are preferred.
- Excellent writing and communication skills
- Strong ability to work on multiple projects simultaneously, balancing priorities, and work on cross-functional teams
Some Travel Required
Join us for competitive benefits and development opportunities in a progressive and supportive environment. Help us improve our service, and the experiences of our patients and colleagues. Work with us and together we can be better.
Your Quest career. Seek it out.
All requirements are subject to possible modifications to reasonably accommodate individuals with disabilities. Quest Diagnostics is an Equal Opportunity Employer: Women / Minorities / Veterans / Disabled / Sexual Orientation / Gender Identity or Citizenship.