Statistician
- Location: Waterford
- Hybrid working
- Job Type: Permanent
Purpose of the Role:
Provide stats guidance and direction across the MSAT DP network on approaches and continuous improvement plans.
- Design, deploy and sustain best practices in statistical approaches/modelling and utilisation across MSAT DP network.
- Participate and be lead input provider of DP MSAT on Global policy and procedure updates/forums to assure DP TT/NPI/LCM activity considerations are undertaken in same.
- Participate in the development of site statistical systems, and rollout of support across the DP MSAT to upskill across the network.
- Enable sites within the DP MSAT organisation in designing and deploying systems to transform data into useful process information.
- Champion statistical best practices across the site and within the Sanofi MSAT DP network.
- Provide oversight of the methods in which statistical expertise are applied to activities within the MSAT DP.
Job Requirements
- Provide statistical guidance for method validations and method transfers in the areas of accuracy, precision, linearity, equivalence testing (T OST), power and sample size.
- Support major process engineering and/or quality investigations from a statistical perspective to ensure data is available to provide focused information as part of the problem- solving processes.
- Develop the sites statistical process control (SPC) systems to help process engineers build a data led understanding, including OCS/PCS, of the state of control of different manufacturing and laboratory processes.
- Interface with site's PCS team and site's automation team to understand how data is captured and how available data relates to product and process critical process parameters.
- Support the building of statistically based sampling plans in inspection areas.
- Use the appropriate statistical tools for analysing many types of data problems. These problems can range from selecting random data samples to designing statistical experiments.
- Construct and apply various prediction (regression) equations including the application of statistical process control procedures, covering univariate and multivariate samples.
- Understand and deploy processes for data presentation (frequency tables, histograms and box plots), descriptive statistics (mean, median, mode, range, variance, standard deviation, quartile and quantile), basic normal probability theory and statistical hypothesis testing. Several one-sample testing procedures-such as the binomial test, normal test and the t-test-are detailed, along with confidence intervals. The appropriate tests of hypotheses for (one -sample) variance problems are also included.
- Analyse and interpret statistical data to identify significant differences in relationships among sources of information.
- Develop an understanding of fields to which statistical methods are to be applied to determine whether methods and results are appropriate.
- Evaluate sources of information to determine any limitations in terms of reliability or usability.
- Evaluate the statistical methods and procedures used to obtain data to ensure validity, applicability, efficiency, and accuracy.
- Identify relationships and trends in data, and any factors that could affect the results of research.
- Plan data collection methods for specific projects and determine the types and sizes of sample groups to be used.
- Provide guidance on preparation of data for processing by organising information, checking for any inaccuracies, and adjusting and weighting the raw data.
- Lead & provide guidance on reporting of results of statistical analyses, including information in the form of graphs, charts, and tables.
- Design research projects that apply valid scientific techniques and use information obtained from baselines or historical data to structure uncompromised and efficient analyses.
- Develop and test experimental designs, sampling techniques, and analytical methods.
- Examine theories, such as those of probability and inference, to discover mathematical bases for new or improved methods of obtaining and evaluating numerical data.
- Establish and maintain internal / external network relationships in the area of statistics.
Qualifications
- Bachelors in Statistics, Biostatistics or Applied Maths with minimum 5 years prior work experience in Statistics OR
- Masters or PhD degree in Statistics, Biostatistics or Applied Maths.
Experience
- 8+ years' experience in as a statistician, including a minimum of 3 years in a GMP regulated site.
Skills and Knowledge
- Excellent understanding of the applications of statistics in a manufacturing environment.
- Excellent problem solving and data analytical skills.
- Experienced user of statistical analysis packages, particularly Minitab / JMP.
- Strong influencing, communication and interpersonal skills, with experience working across multidisciplined and multicultural teams.
- Flexible with the ability to prioritise work in a dynamic environment.
- Familiar with regulatory statistical expectations.
- Process understanding of the various stages of sterile manufacturing through to inspection and packaging.
Designation Duty
- Site Statistical Lead and MSAT MT&I Manager as required.
Personal Characteristics
- High Energy and Commitment.
- Ability to work independently.
- Comfortable influencing across multiple stakeholders & department teams at international and corporate level.
- Strong ability to coach and mentor others.
- Effective Change agent and ability to manage resistance to change.
- Capable of resolving issues of conflict effectively.
- Strong communicator.
Pursue progress. Discover extraordinary.
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At Sanofi, we provide equal opportunities to all regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, or gender identity.
Watch our ALL IN video and check out our Diversity Equity and Inclusion actions at sanofi.com!
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Diversity und Inklusion sind in den Grundwerten von Sanofi verankert und spiegeln sich in unserer Arbeitsweise wider. Wir respektieren die Vielfalt unserer Belegschaft in Hinsicht auf ihre Herkunft, Erfahrungen und Lebensweisen. Wir erkennen die Bereicherung, die diese Vielfalt birgt, und fördern Inklusion sowie eine Arbeitsumgebung, in der diese Unterschiede sich weiter entwickeln können, zur Stärkung des Lebens unserer Mitarbeiter, Patienten und Kunden.
