Job Description Summary
Work closely with project teams (FPL, DPPL, APL) and innovation teams to drive use of statistical and data science methods in combined lab and computational experimental planning, analysis and reporting for the development of synthetic molecule formulations. Enable scientists to independently work with basic statistical methods while directly supporting advanced statistical and AI tasks. Apply statistical and data science methods to generate business insights for continuous improvement and enhancing our ways of working.Job Description
Your responsibilities will include, but are not limited to:
Minimum Requirements:
·Minimum: Advanced degree in mathematics, physical science, or relevant discipline (PhD or equivalent) with a strong focus on statistical and data science techniques. Desirable: Ph.D. in scientific or relevant discipline or equivalent
·Expert in statistical experimental design such as Design of Experiments, Bayesian optimization etc.
·Expert in multi-variate data analysis
·Experienced in AI with particular focus on machine learning application to data driven models and predictive analytics
·Understanding of the development of pharmaceutical formulations including solid understanding of QbD principles
·Interdisciplinary thinking and interest in collaboration with other functions.
·Successfully demonstrated track record of creativity and problem solving in projects.
·Knowledge of relevant GLP, GMP regulations and policies.
·Strong presentation skills and scientific/technical writing skills.
·Good project management skills.
·Good communication skills, organizational, planning and negotiation skills.
·Excellent coaching skills
·Experience in programming, e.g. python, R etc.
Skills Desired
Apache Hadoop, Applied Mathematics, Big Data, Curiosity, Data Governance, Data Literacy, Data Management, Data Quality, Data Science, Data Strategy, Data Visualization, Deep Learning, Machine Learning (Ml), Machine Learning Algorithms, Master Data Management, Proteomics, Python (Programming Language), R (Programming Language), Statistical Modeling