Associate Principal Scientist Statistical Programming- Oncology, PKPD- Hybrid

Job Description

Responsibilities:

This position provides high quality statistical programming analysis and reporting deliverables for global PK modeling and simulation stakeholders spanning all therapeutic areas.  The programming analyst will 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.   The programming analyst will take on a data stewardship leadership role and be accountable for the creation of modeling data from original data source(s) to final modeling dataset.  The programming analyst will be a key collaborator with modelers, statisticians and other project stakeholders and is expected to execute project plans efficiently and oversee the work of other team members when opportunities arise.

Primary Activities:

• Programmatically synthesize clinical / preclinical data into analysis ready structures from varied data sources
• Create modeling-ready datasets by integrating PK, ADA, 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

Education and Minimum Requirement:

BA/BS in Computer Science, Statistics, Applied Mathematics, Life Sciences, Engineering or related field plus 9 years SAS programming experience in a clinical trial environment

MS in Computer Science, Statistics, Applied Mathematics, Life Sciences, Engineering or related field plus 7 or more years SAS programming experience in a clinical trial environment

Department Required Skills and Experience:

• 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 and 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

Position Specific Required Skills and Experience:

• Significant expertise in SAS and clinical trial programming including data steps, procedures, SAS/MACRO, SAS/GRAPH
• Designs and develops complex programming algorithms
• Ability to comprehend analysis plans which may describe methodology to be programmed; understanding of statistical or pharmacokinetic terminology and concepts; Implements statistical methods not currently available through commercial software packages.
• 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
• Efficiently manipulates clinical trial datasets including complex data preprocessing, filtering, and manipulation; programming expertise with clinical endpoint data (efficacy and safety) and pharmacokinetic data (raw concentration data, derived PK parameters).

** Preferred Skills and Experience:

• Familiarity with pharmacokinetics modeling and simulation datasets and analyses
• Experience with at least one other software than SAS (e.g., R, Splus, NonMem)
• Good working knowledge of reporting processes (SOPS) and software development life cycle (SDLC)
• Utilizes and contributes to the development of standard departmental SAS macros
• Ability and interest to work across cultures and geographies
• Ability to complete statistical programming deliverables through the use of global outsource partner programming staff
• Active in professional societies

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U.S. Hybrid Work Model

Effective September 5, 2023, employees in office-based positions in the U.S. will be working a Hybrid work consisting of three total days on-site per week, Monday - Thursday, although the specific days may vary by site or organization, with Friday designated as a remote-working day, unless business critical tasks require an on-site presence.This Hybrid work model does not apply to, and daily in-person attendance is required for, field-based positions; facility-based, manufacturing-based, or research-based positions where the work to be performed is located at a Company site; positions covered by a collective-bargaining agreement (unless the agreement provides for hybrid work); or any other position for which the Company has determined the job requirements cannot be reasonably met working remotely. Please note, this Hybrid work model guidance also does not apply to roles that have been designated as “remote”.

The Company is required to provide a reasonable estimate of the salary range for this job in certain states and cities within the United States. Final determinations with respect to salary will take into account a number of factors, which may include, but not be limited to the primary work location and the chosen candidate’s relevant skills, experience, and education.

Expected US salary range:

Available benefits include bonus eligibility, long term incentive if applicable, health care and other insurance benefits (for employee and family), retirement benefits, paid holidays, vacation, and sick days. A summary of benefits is listed here.

San Francisco Residents Only: We will consider qualified applicants with arrest and conviction records for employment in compliance with the San Francisco Fair Chance Ordinance

Los Angeles Residents Only: We will consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance

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