CMC Statistician

Bayer•Berkeley, CA

3d•Hybrid

About The Position

At Bayer, we are driven by the vision of solving the world's toughest challenges and striving for a world where 'Health for all, Hunger for none' is a reality. We are looking for a CMC Statistician to perform advanced statistical analyses and data mining. This role involves developing and testing experimental designs, sampling techniques, and analytical methods. The statistician will query large sets of structured and unstructured biological and biotechnology data, clean and validate data for accuracy and completeness, and develop mathematical and statistical models to simulate biologic processes. The role also includes designing experiments for biologics, performing data analysis using statistical methods and machine learning tools, monitoring biological systems, and making recommendations for process control and optimization.

Requirements

Ph.D. in Statistics, Applied Mathematics, or a closely related quantitative field and 1 year of experience using Python and R to design, develop, and deliver statistical models and machine learning algorithms using biotech data sets.
Experience monitoring biological systems and making recommendations regarding process control and optimization.
Experience using gitlab & Jupyter to transform semi-structured and unstructured biological process sensor data and biological product analytical data into features for model development.
Experience supporting biological processes, product development & GMP cell therapy manufacturing applying design of experiments & advanced statistical data analysis.
Experience querying biological process data & performing data mining and visualization in GCP, AWS and/or Domino.
Experience developing models with genomic data to conduct time series & ANOVA analysis for biological data sets.
Master’s degree in Statistics, Applied Mathematics or closely related quantitative field and 3 years of the stated experience will also be accepted.

Responsibilities

Perform advanced statistical analyses and data mining.
Develop and test experimental designs, sampling techniques, and analytical methods.
Query large sets of structured and unstructured biological and biotechnology data from disparate sources.
Clean and validate data to ensure accuracy, completeness, and uniformity for statistical analysis.
Develop mathematical and statistical models to simulate biologic processes, functions, and behaviors, and report results.
Design experiments for biologics and perform data analysis using statistical methods and machine learning tools.
Monitor biological systems and make recommendations regarding process control and optimization.
Transform semi-structured and unstructured biological process sensor data and biological product analytical data into features for model development using gitlab & Jupyter.
Support biological processes, product development, and GMP cell therapy manufacturing by applying design of experiments and advanced statistical data analysis.
Query biological process data and perform data mining and visualization in GCP, AWS, and/or Domino.
Develop models with genomic data to conduct time series and ANOVA analysis for biological data sets.