Associate Principal Scientist, Statistical Programming

Merck•North Wales, PA

1d•Hybrid

About The Position

Provide high quality statistical programming analysis and reporting deliverables for global PK modeling and simulation stakeholders in the Oncology therapeutic area. Gather and interpret user requirements, retrieve the required data, transform the data into modeling-ready analysis datasets, and develop tables and figures according to the modeling analysis plans. Lead the data stewardship and take accountability for the creation of modeling data from original data source(s) to final modeling dataset. Act as a key collaborator with modelers, statisticians and other project stakeholders and execute project plans efficiently and oversee the work of other team members when opportunities arise. Programmatically synthesize preclinical / clinical data into analysis ready structures from varied data sources. Create modeling-ready datasets by integrating PK, PD and covariate data. Produce tables and graphics for inclusion in study reports and regulatory submissions. Ensure programmatic traceability from data source to modeling result. Support the development of programming standards to enable efficient and high-quality production of programming deliverables. Produce SAS transport files and associated documentation for regulatory submissions. Represent statistical programming on process improvement activities.

Requirements

Must have a Bachelor’s degree (or US equivalent) in Computer Science, Statistics, Applied Mathematics, Life Sciences, Engineering, Pharmaceutical Sciences, or related field plus 9 years SAS programming experience in a clinical trial environment OR a Master’s degree (or US equivalent) in Computer Science, Statistics, Applied Mathematics, Life Sciences, Engineering, Pharmaceutical Sciences, or related field plus 7 years SAS programming experience in a clinical trial environment.
Must possess significant expertise in SAS and clinical trial programming including data steps, procedures, SAS/MACRO, SAS/GRAPH; and programming expertise with clinical endpoint data (efficacy and safety) and pharmacokinetic data (raw concentration data, derived PK parameters).
Ability to design and develop complex programming algorithms; to efficiently manipulate clinical trial datasets including complex data preprocessing, filtering, and manipulation.
Demonstrated ability to work in an exploratory environment, handling non-standard data in a variety of formats with minimal requirements.
Knowledge of pharmaceutical development processes.
Ability to comprehend analysis plans which may describe methodology to be programmed.
Understanding of statistical or pharmacokinetic terminology and concepts; and ability to implement statistical methods not currently available through commercial software packages also required.
Must possess broad knowledge and significant experience in developing analysis and reporting deliverables for R&D projects (data, analyses, tables, graphics, listings).
Ability to lead at a program level.
Ability to determine approach and ensure consistency and direct development of others when opportunities arise.
Ability to engage key stakeholders required.
Must possess strong project management skills; excellent interpersonal skills; ability to negotiate and collaborate effectively; and excellent written, oral, and presentation skills.

Responsibilities

Provide high quality statistical programming analysis and reporting deliverables for global PK modeling and simulation stakeholders Oncology therapeutic area.
Gather and interpret user requirements, retrieve the required data, transform the data into modeling-ready analysis datasets, and develop tables and figures according to the modeling analysis plans.
Lead the data stewardship and take accountability for the creation of modeling data from original data source(s) to final modeling dataset.
Act as a key collaborator with modelers, statisticians and other project stakeholders and execute project plans efficiently and oversee the work of other team members when opportunities arise.
Programmatically synthesize preclinical / clinical data into analysis ready structures from varied data sources.
Create modeling-ready datasets by integrating PK, PD and covariate data.
Produce tables and graphics for inclusion in study reports and regulatory submissions.
Ensure programmatic traceability from data source to modeling result.
Support the development of programming standards to enable efficient and high-quality production of programming deliverables.
Produce SAS transport files and associated documentation for regulatory submissions.
Represent statistical programming on process improvement activities.