Associate Principal Statistical Programmer, Observational Research and Real World Evidence Job - United States
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Merck & Co., Inc. Kenilworth, N.J., U.S.A. known as Merck in the United States and Canada, is a global health care leader with a diversified portfolio of prescription medicines, vaccines and animal health products. The difference between potential and achievement lies in the spark that fuels innovation and inventiveness; this is the space where Merck has codified its 125-year legacy. Merck’s success is backed by ethical integrity, forward momentum, and an inspiring mission to achieve new milestones in global healthcare.
Merck is on a quest for cures and is committed to being the world’s premier, most research-intensive biopharmaceutical company. Today, we’re doubling down on this goal. Merck Research Laboratories is a true scientific research facility of tomorrow, and will take Merck’s leading discovery capabilities and world-class small molecule and biologics R&D expertise to create breakthrough science that radically changes the way we approach serious diseases.
This position provides high quality statistical programming analysis and reporting deliverables for the Merck Center for Observational and Real World Evidence (CORE). The statistical programming analyst utilizes strong SAS expertise to efficiently manipulate electronic healthcare databases to discover disease prevalence and risk factors, describe drug utilization patterns and disease progression, support market research, and answer clinical development questions.
In this role, the statistical programming analyst will gather and interpret user requirements from CORE scientists (e.g. epidemiologists and outcomes research scientists), retrieve the required data from electronic healthcare databases, and develop disease cohorts, analytical datasets, tables and figures and perform validation activities following departmental SOPs. The programming analyst will be a key collaborator with CORE scientists to execute project plans efficiently and oversee the work of other team members when opportunities arise.
- BA/BS in Computer Science, Statistics, Applied Mathematics, Life Sciences, Engineering or related analytical field plus a minimum of 9 years SAS programming experience
- MS in Computer Science, Statistics, Applied Mathematics, Life Sciences, Engineering or related analytical field plus 7 years SAS programming experience
- Excellent interpersonal skills and ability to negotiate and collaborate effectively
- Excellent English written, oral, and presentation skills
- Broad knowledge and significant experience in developing analysis and reporting deliverables for R&D 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
- Significant expertise in SAS and health care programming including data steps, procedures, SAS/MACRO, SAS/GRAPH; systems and database expertise
- Designs and develops complex 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 of observational research or statistical terminology and concepts; implements observational methods not currently available through commercial software packages
- 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
- Experience ensuring process compliance and deliverable quality
- Team oriented with demonstrated history of teamwork and collaboration; enjoying diversity, respect and integrity
- Familiarity with the fields of Outcomes Research and Epidemiology
- Experience working with coding systems such ICD-9, READ/OXMIS, and ICD-10
- Knowledge in CDISC SDTM and ADaM standards
- Oracle SQL experience
- Efficiently manipulates large databases including complex data preprocessing, filtering and manipulation; experience with sample strategies for large databases;
- Demonstrated success in the assurance of deliverable quality and process compliance. Strong working knowledge of reporting processes (SOPs) and software development life-cycle (SDLC)
- Basic understanding of statistics, clinical and data management concepts as applied to drug/vaccine development within the pharmaceutical industry
- Experience assuring programming consistency across protocols and projects, directing the program development effort of other programmers; experience as a programming mentor
- 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
- An interest to advance career by investing in development activities and taking on tasks with increasing levels of challenge and responsibility
- Ability to anticipate stakeholder requirements
- Experience developing and managing a project plan using Microsoft Project or similar package
- Ability and interest to work across cultures and geographies
- Active in professional societies
- Experience in process improvement; utilizes and contributes to the development of standard departmental SAS macros and tools
Your role at Merck is integral to helping the world meet new breakthroughs that affect generations to come, and we’re counting on your skills and inventiveness to help make meaningful contributions to global medical advancement. At Merck, we’re inventing for life.
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Job: Statistical Programming
Job Title:Assoc Prin.Scientist Stat.Programming
Primary Location: NA-US-PA-Upper Gwynedd
Other Locations: NA-US-NJ-Rahway
Employee Status: Regular
Number of Openings: 1
Company Trade Name:Merck
Nearest Major Market: Philadelphia
Job Segment: Epidemiology, Medical, Public Health, Statistics, Engineer, Healthcare, Data, Engineering