Non-Clinical CMC Statistician, FSP

IQVIA•Durham, NC

14h•Remote

About The Position

Data Sciences Staffing Solutions (DSSS), a unit within IQVIA, offers fully embedded resources to sponsors through a Functional Service Provider (FSP) partnership. This model provides the benefits of working for a global CRO while collaborating directly with cross-functional sponsor teams from world-class pharmaceutical and biotech companies. The Non-Clinical Statistician will apply statistical design, tools, and techniques to support the process, analytical method, and formulation development of medical or pharmaceutical products throughout their lifecycle.

Requirements

Doctorate Degree in Statistics or a related field plus 2 years minimum of relevant applied statistics experience OR Master’s Degree in Statistics or a related field plus 5 years minimum of relevant applied statistics experience OR Bachelor’s Degree in Statistics or a related field plus 10 years minimum of relevant applied statistics experience.
Proficient in non-clinical applications, including particle size and distribution, in-vitro bioequivalence assessments, analytical method optimization and validation, process development and platform characterization, and stability studies to understand, control, and ensure product quality.
Experience and/or training in design of experiments, including optimization or robustness experimental designs.
Proficient in statistical techniques commonly used in pharmaceutical manufacturing operations, such Statistical Process Control, Process Capability Analysis, Measurement System Analysis, Acceptance Sampling, Non-linear and Linear Regression, Significance Testing, and Simulation.
Proficient in SAS and/or R programming including data manipulation, macros, functions, statistical and graphical packages, and quality output production.
Good understanding of pharmaceutical development and CMC activities in a regulatory context, including GMP and Quality by Design framework.
Excellent communication and collaboration skills.
Demonstrated ability to work independently and pro-actively to deliver top quality work product.

Nice To Haves

Skills in machine learning or Bayesian methods.
JMP or R-Shiny skills.

Responsibilities

Collaborate with subject matter experts to design experimental studies, plan and perform statistical analysis, and document results in technical reports, in support of business decisions, regulatory submissions and compliance.
Provide statistical support for a wide range of non-clinical applications, including: particle size and distribution, in-vitro bioequivalence assessments, analytical method optimization and validation, process development and platform characterization, and stability studies to understand, control, and ensure product quality.
Ensure compliance with regulatory and ISO requirements for the statistical methods employed.
Develop, implement, and maintain statistical tools used to support product life cycle activities.
Promote good statistical practice across the team and mentor colleagues in statistical techniques and software tools.
Stay up to date on best practices, industry trends, and regulatory guidance.
Support other non-clinical statistical applications, when needed.
Support regulatory audits by responding to questions during on-site inspections and providing written responses to clarify statistical approaches or perform additional analyses.

Benefits

Home-based remote working opportunities.
Work/life balance as well as flexible schedules.
Collaborating with motivated, high-performance, statistical and research teams.
Technical training and tailored development curriculum.
Research opportunities that match your unique skillset.
Promising career trajectory.
Job stability: long-term engagements and re-deployment opportunities.
Focus on bringing new therapies to market rather than project budgets and change orders.
Experience with regulatory submissions.
Engaging, fast-paced environment.
Good work-life balance.
A range of health and welfare and/or other benefits.
Incentive plans, bonuses, and/or other forms of compensation.