Description

Job Title:

RWE Data Scientist (contractor), V&E Real World Evidence Analytics

• Will be working with Claims, EHR, relational database, open or closed source or big EHR systems
• Projects can be in any database like optum market scan, comodo, relational database etc so knowledge of large scale Database and EHR systems is a must have
• Coding extracting and analyzing data
• R programming exp
• Hands on data analytics and good at presentation to the team
• Exp with some administrative health and coding systems
• Machine learning is a plus
• visualization
• Independent researcher as well as  a statistician
• Candidate will tap in to large data bases, claims, EMR and process data
• Independent research thinking
• Advance analytical skills to work on large scale databases
• Protocol development
• Targeted literature reviews
• Summarize results in easy way so that diff teams can understand
• Statistical methodologies
• Advance programming skills
• Some clinical exposure needed
• Need some one who can work hands on programming and other things
• SAS programming exp
• Python exp
• Current project is being done in python so python or R skills are needed for this role
• Strong PhD candidate with exp in Health Economics and Outcomes research, Epidemiology, health services research will be a good fit
• Prior knowledge in oncology therapeutic area will be a plus

Purpose:

• Role is responsible for designing, planning, and executing large scale data analysis, and algorithm development to identify gaps in the care continuum and to measure impact using RWD.
• This work highlights the value of utilizing real world data to inform or address strategic questions in the disease areas of interest to Client.
• The role involves the application of statistical theories, analytical methods, and technical programming skills to analyze clinical, survey, claims, and electronic medical record databases.
• Role supports the department as a technical subject matter expert on RWE analytics; candidate is expected to act as point of contact for the assigned therapeutic area (TA) on analytical needs, proactively mitigating, resolving and triaging issues and reducing the operational complexity needed.
• Candidate is expected to standardize coding convention, and processes to increase efficiency. Candidates must be adept at breaking down complex data into easily understood language and/or visualization for less technical audiences.
• Candidates should also be creative in the use of RWD and propose solutions to answer business questions.

Responsibilities: 

• The candidate is expected to have the potential to be the analytics lead for the assigned therapeutic area (TA) to mitigate, resolve and triage analytical complexities
• Presenting results of analysis and contribute presentation of findings and key takeaways for various audiences
• Identifying appropriate internal and external data resources and external expertise to execute strategies and research activities
• Executing analysis plans and providing consultation to design as needed
• Work with Medical engagement to understand key impact variables and use RWD to quantify and operationalize these variables
• Responsibility and accountability for meeting timelines in complex matrix structure. This will require developing and maintaining effective cross-functional working relationships to assure effective teamwork and overseeing problem solving within the analytical team
• Interactions with Medical Engagement, Business Unit TAs, HEOR, and RWE CoE regarding findings and with other members of the Analytical team that perform QC activities on their studies
• Translating TA business needs into project concepts to develop supporting data dictionary and corresponding analysis

Qualifications:

• Master’s degree in Statistics or related discipline required, PhD in statistics or closely related discipline (e.g., Health Economics and Outcomes research, Epidemiology, health services research etc.) preferred
• Minimum of 1-2 years’ experience in analytics programing (SAS, SQL, R, Python) required. The candidates with Python and machine learning experience are preferred.
• Ability to incorporate production code macros required, ability to execute programming assignments and problem solve issues independently, and ability to present complex research and data clearly to stakeholders.
• Experience and/or training in the application of advanced scientific and analytical methods in real world evidence generation
• Ability to perform urgent analyses that are needed with short turnaround time and interact with internal and external collaborative partners on joint projects
• Professional training in a healthcare field, experience in analysis of large medical claims datasets or prior experience in the UNIX/Hadoop environment preferred