Statistical Programmer II (R Prog + SAS + SQL)

Description

Statistical Programmer II

Syneos Health is a leading fully integrated biopharmaceutical solutions organization built to accelerate customer success. We translate unique clinical, medical affairs and commercial insights into outcomes to address modern market realities.

Our Clinical Development model brings the customer and the patient to the center of everything that we do. We are continuously looking for ways to simplify and streamline our work to not only make Syneos Health easier to work with, but to make us easier to work for.

Whether you join us in a Functional Service Provider partnership or a Full-Service environment, you ll collaborate with passionate problem solvers, innovating as a team to help our customers achieve their goals. We are agile and driven to accelerate the delivery of therapies, because we are passionate to change lives.

Discover what our 29,000 employees, across 110 countries already know:
WORK HERE MATTERS EVERYWHERE

Why Syneos Health

Job responsibilities
Uses SAS or other software to generate summary tables, data listings, graphs and derived datasets as specified in the statistical analysis plan and programming specifications.
Works to ensure that outputs meet quality standards and project requirements.
Performs validation programming and works with other Statistical Programmers, Biostatisticians, and other project team members to resolve discrepancies or any findings.
Keeps project team members informed of programming progress and issues requiring their attention.
Follows applicable SOPs, WIs, and relevant regulatory guidelines (e.g. ICH).
Maintains well organized, complete, and up-to-date project documentation, and verification/quality control documents and programs ensuring inspection readiness.
Manages scheduling and time constraints across multiple projects, sets goals based on priorities from management, and adapts to timeline or priority changes by reorganizing daily workload.
May develop specifications for datasets and outputs according to statistical and Sponsor requirements. Anticipates and addresses potential programming issues, reflects forethought, establishes the basis for efficient programming, accurately defines all variables to be accepted by peer review and sponsor/requestor with little rework.
Prepares in advance for internal meetings, contributes ideas, and demonstrates respect for opinions of others.
Displays willingness to work with others and assist with projects and initiatives as necessary to meet the needs of the business.
Completes project programming activities within timeframe allotted by Lead Statistical Programmer and/or management.
May act as the Lead Statistical Programmer, directs the programming activities of other programming personnel and monitors progress on programming deliverables.
Assists with the transfer of deliverables.
Performs other work-related duties as assigned.
Minimal travel may be required.

Qualifications

What we re looking for
Undergraduate Degree, preferably in a scientific or statistical discipline; In lieu of degree, an equivalent combination of education and demonstrated programming experience.
Proficiency in programming in SAS or other required software, preferably in a clinical trial environment.

Requirement - R Programmer(s): External Anonymized Dataset production
Require Statistical Programmer II (2-4yrs); Sr Statistical Programmer (5-8yrs); Principal Stat Programmer (8yrs above) relevant experience in Clinical SAS
SAS/SQL, R programming skills
Hand on experience in Anonymization of Clinical Datasets will be given weightage
Experience in Github / GitLab preferred
SDTM / ADaM Theoretical knowledge and SDTM hands on experience will be value added.
Excellent written and verbal communications skills.
Capable Programmer(s) with proven R (R Studio) skills. SQL experience will be useful to write conditions for data redactions. As code is managed using Git\Gitlab any experience in this area will also be useful. Some knowledge of Python may be useful e.g. to look at code / outputs.
Good eye for detail to review clinical data pre- and post-processing from the anonymization ruleset tool. This includes review for Personal Protected Information (PPI) based on the ruleset provided or variables/observations do not present in the ruleset.
Knowledge of the drug development process (Phase I through IV) and general regulatory requirements.
study lead experience and capable of managing multiple studies.
Excellent written and verbal communication skills.
Ability to read, write, speak, and understand English.