The Senior Principal Statistician is a highly strategic Quality role that will help to align best practices of using data analytics and statistical analysis for technical and cross-functional/cross company business issues. This role is expected to provide in depth technical knowledge and leadership in the areas of analytical data analysis to support the Akebia Quality Control and Quality Assurance functions. The position requires an experienced pharmaceutical scientist / with a proven track record of applying statistical analysis techniques in the areas of Quality Control, specifically related to release and stability data.
This position will serve to support growth and expansion of Akebia’s Quality Control function. The ideal candidate will develop, implement, and drive improvement of data analytics and business processes that include but are not limited to both process and method capability analysis. The incumbent will identify risks and adverse trends related to analytical data for both clinical and commercial products. The Sr. Principal Statistician will work extensively with colleagues inside and outside Quality to drive improvements related to the analytical data analysis and trending to support the Global Stability and Quality Operations teams. The Sr. Principal Statistician will support investigations and expiry extension efforts as well as contribute to routine data monitoring and completion of critical regulatory filings and requirements for both clinical and commercial objectives (e.g., Annual Product Review, stability trending reports, expiry extension). Sr. Principal Statistician may lead high level cross functional teams utilizing project management skills to implement and improve key business processes and will oversee activities of lower-level employees.
- Develop and standardize complex statistical analysis techniques to support analytical evaluation of clinical and commercial analytical data to support routine trending, identification of eroding trends, technology transfer and routine commercial product analyses.
- Make use of statistical software packages and other data manipulation software packages in the evaluation of Product Quality Review, in-process product, and special investigation data on a regular basis for all products.
- Lead teams through complex problem-solving methods and perform in-depth analysis of tangible and intangible factors to determine cause and effect.
- Work collaboratively across functions to collect, trend, and report analytical data to be utilized to support investigations, validations, and process improvements.
- Design and develop statistical applications for use by others for ongoing monitoring and analysis of internal/external data.
- Work with colleagues within and outside Quality to drive and embed improvements to analytical trending processes throughout the organization.
- Analyze data from investigation evaluations, summarizes conclusions and makes recommendations for further work where necessary.
- Generate quarterly reports analyzing data from within Akebia’s supply network.
- B.S degree
- 8+ years of pharmaceutical industry experience
- A Master’s of Science Degree
- 6+ years of pharmaceutical industry experience
- B.S in Statistics, Engineering, Mathematics, or one of the life sciences
- Pharmaceutical Development, Statistical/Data analytic support of commercial manufacturing and/or research experience
- Experience working with multiple manufacturing sites/laboratories, including contract manufacturing / laboratories is highly desired.
- Familiarity with data analytics tools
- Expert understanding of CPV and its applications
- Ability to understand and simplify complex processes
- Impact across both commercial and development programs
- Knowledge of cGMP, ICH and Regulatory CMC guidance documents specific to the role.
- Lean/six-sigma training and applications experience. Able to coach less experienced colleagues within the function
- Thorough knowledge of pharmaceutical testing
- Strong knowledge of the relevant cGMP, ICH and global Regulatory CMC guidance documents applicable to the function.