Bachelor Degree in Statistics / Maths / Natural Science / Chemical or M.Sc or PhD
Job Description :
# 3+ Years experience in manufacturing, Proven process understanding (Pharma, GMP, Regulatory aspects).
# Proven experience of applied statistics is a must, e.g. in the field of DoEs and multivariate data analysis.
# Experience in the following software is a plus: SAS, R, Minitab, SIMCA-P+, Modde, JMP, SPSS.
Roles & Responsibilities :
# Process Validation and Transfers:
- Statistical analysis of process validation data for demonstrating validity and equivalence.
- Contribute to risk assessments, e.g. FMEA or risk matrix.
- Planning and evaluation of Design of Experiments (DoEs) in the frame of the Novartis Quality by Design validation strategy.
# Trending analysis in the frame of Continuous Process Verification.
- Implementation and application of Statistical Process Control principles, e.g. control charts, and other pattern recognition techniques..
- Support the compilation of Annual Product Review (APR) / Product Quality Reviews (PQRs).
- Facilitate and enable (Multivariate) process monitoring and control principles, e.g. by Multivariate Data Analysis (MVDA).
- Review of stability data and definition of Internal Release Limits (IRL).
# Support critical root cause investigation (e.g. observation of Out Of Spec (OOS) and other deviations):
- Support the analysis of complex data sets to facilitate Rapid Root Cause Investigation (rRCI)
- Accountable for providing meaningful statistical conclusions.
# Analytical method validation and transfer, in particular Process Analytical Technology (PAT) methods:
- Support the design of an analytical robustness test, e.g. by means of DoE.
- Statistical assessment of method validation data and technology and process transfer across sites
- Development and validation of multivariate models for on-line PAT methods.
# Enable Process improvement initiatives (also in alignment with operational excellence organization and methodologies (e.g. IQP, Six Sigma, Lean Manufacturing):
- Capability and stability assessments
- Hypothesis testing
- Models for facilitating process improvements, e.g. DoE, MVDA, Computational Fluid Dynamics (CFD), multi linear curve fitting etc.
- Enable the Site to have the necessary competencies in advanced applied statistical tools, cross functionally (MS&T, manufacturing, QA, QC, operational excellence, ..) by designing and delivering training on available tools and how to use them in practice, providing ongoing coaching.
- Instruct how to collect (e.g. sampling plans which are statistically meaningful), set up and interpret data sets and statistical results highlighting constraints and limitations.
# Interacts with internal and external Reg bodies and Health Authorities, as well as internal functions (development organization, RegCMC, QA/QC, Engineering, global MS&T) as appropriate (e.g. during inspections, investigations etc.) in statistical aspects of data analysis and rationales.