responsibilities :

• Promoting the application and adoption of statistical analysis, machine learning modeling and data science capabilities for Bioengineering and Bioprocessing R&D through strong technical and interpersonal abilities
• Partnering with leading R&D scientists to advance discovery, characterization, development, and manufacture of natural products through data science
• Providing statistical and machine learning expertise, and collaborate with scientists to improve hypothesis formulation, experimental design, data collection, modeling, process design and interpretation of complex datasets to enable data-driven decisions
• Developing and deploying end-to-end data engineering and data science pipelines at scale for users with diverse backgrounds in chemical and biological disciplines

Qualifications :

• Extensive experience with big data engineering, descriptive statistics, dimensionality reduction, predictive modelling and validation (mixed-models, non-linear regression, principal components, cross-validation techniques, etc.)
• Knowledge of simulation techniques and optimization methods with multiple constraints
• Understanding of high-performance machine learning algorithms (decision trees, neural networks, SVM etc.).
• Solid expertise in a scientific programming language (e.g. R, Python) preferably in a HPC or Cloud environment.
• Written and verbal communication skills and the ability to successfully collaborate and lead projects with colleagues from diverse technical backgrounds
• Critical thinking and strong problem-solving skills