Associate Principal Statistical Programmer, Real World Evidence- Hybrid

Job Description

This position provides high quality statistical programming analysis and reporting and regulatory submission deliverables for Real World Evidence projects across our company's Biostatistics and Research Decision Sciences (BARDS) group.  The associate principal statistical programmer utilizes strong expertise in multiple programming languages including SAS and R to efficiently manipulate electronic healthcare databases to discover disease prevalence and risk factors, describe drug utilization patterns and disease progression, answer clinical development questions, and support regulatory submissions.  In this role, the associate principal statistical programmer will gather and interpret user requirements from epidemiologists, retrieve the required data from electronic healthcare databases, and develop disease cohorts, analytical datasets, tables, figures, and submission deliverables and perform validation activities following departmental standard operating procedures.   The associate principal statistical programmer will be a key collaborator with Biostatistics and Research Decision Sciences (BARDS) epidemiologists and oversee the work of other team members when opportunities arise. 

Position Qualifications:

Education Minimum Requirement:  

• MS in Computer Science, Statistics, Applied Mathematics, Life Sciences, Engineering or related analytical field plus minimum 7 yrs experience in multiple programming languages including SAS and R

• BA/BS in Computer Science, Statistics, Applied Mathematics, Life Sciences, Engineering or related analytical field plus 9 years' experience in multiple programming languages including SAS and R

Required Experience and Skills:

• Excellent interpersonal skills and ability to negotiate and collaborate effectively

• Excellent written, oral, and presentation skills

• Broad knowledge and significant experience in developing analysis and reporting deliverables for Research & Development projects (data, analyses, tables, graphics, listings)

• Strong project management skills; leadership at a program level; determines approach and ensures consistency and directs development of others when opportunities arise; ability to engage key stakeholders

• Expertise in SAS and R Real World Evidence programming including data processing, statistical procedures and graphing and tabulation techniques; systems and database expertise

• Solid Real World Evidence and Real World domain knowledge

• Designs and develops programming algorithms

• Ability to quickly and effectively learn new program techniques and data structures; capacity to seamlessly assimilate to new projects

• Ability to comprehend data analysis plans which may describe observational research and statistical methodology to be programmed; understanding and implementation of observational research or statistical terminology and concepts; implements observational methods not currently available through commercial software packages.  

• Programming expertise with electronic healthcare databases (electronic medical records and insurance claims); efficiently manipulates large databases including complex data preprocessing, filtering, and manipulation; experience with sampling strategies for large databases

• Unix operating system experience; SQL experience; systems and database experience

• Thrives working in an exploratory environment, handling non-standard data in a variety of formats with minimal requirements

• Demonstrated success in the assurance of deliverable quality and process compliance. Strong working knowledge of reporting processes (SOPs) and software development life-cycle (SDLC);

• An interest to advance career by investing in development activities and taking on tasks with increasing levels of challenge and responsibility

• Team oriented with demonstrated history of teamwork and collaboration; enjoying diversity, respect and integrity

Preferred Experience and Skills:  

• Strategic thinking - ability to turn strategy into tactical activities; design of statistical databases with the end in mind that optimize analysis and reporting and leverage departmental standards and industry best-practices

• Experience in process improvement; utilizes and contributes to the development of standard departmental SAS macros and R code and tools

• Familiarity with the fields of Outcomes Research and Epidemiology including methodologies

• Experience with Common Data Model (CDM)

• Experience in CDISC and ADaM standards

• Experience in version control tools (e.g., git,