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Job Description
We are seeking a Senior Scientist: Process Modelling and Interpretable Machine Learning to drive the development and implementation of advanced analytics solutions in support of manufacturing and quality operations.
A Senior Scientist: Process Modelling and Interpretable Machine Learning will contribute to high-impact projects that require data analytics, advanced modeling, and optimization expertise, and develop and implement advanced analytics, real-time soft sensors, machine learning, advanced process control, and IIoT solutions/capabilities in manufacturing settings to achieve actionable insights and enable continued improvement.
**Key Responsibilities:**
* Contribute to high-impact projects that require data analytics, advanced modeling, and optimization expertise
* Identify high-value opportunities for applying Advanced Analytics, Advanced Process Control (APC), Artificial Intelligence (AI), Machine Learning (ML), and Industrial Internet of Things (IIoT)
* Develop and deploy innovative fit-for-purpose solutions in manufacturing environment
* Drive development of mathematical and machine learning models and support GMP implementation of such analytics solutions
* Apply engineering principles, modeling tools, and experimental skills using data-rich lab/pilot/manufacturing equipment to improve process understanding and facilitate real-time process monitoring and control
* Collaborate with cross-functional teams and key stakeholders, effectively communicate progress to management, and drive project progress in a timely manner
**Basic Qualifications:**
* PhD degree in relevant engineering major, mathematics, or computer science
* Expert-level knowledge in Python
* Experience in R, Matlab, Java Script, or other relevant programming languages
* Ability to perform data engineering on real-world big-data
* Track record in applying data science and machine learning methodologies to real-world data to generate insight and support decision making
* Ability to work collaboratively in diverse cross-functional teams on innovative solutions and tools with an open attitude towards fast learning
* Knowledge of upstream and downstream Biopharmaceutical Manufacturing
* Experience deploying Interpretable Machine Learning or Explainable AI and knowledge of Shapley values and plots
* Demonstrated experience of story-telling with interpretability tools usable by technical experts and non-technical stakeholders
* Use of exploratory analysis tools for abstractions such as feature visualization and attribution that aid scientists in interpreting and explaining machine learning model results
**Preferred Qualifications:**
* Expertise in first principles (thermodynamics, reaction modeling, heat transfer, mass transfer principles), hybrid modeling
* Ability to develop practical process models for real-time applications
* Experience in cloud-based code development and deployment environments such as AWS Sage Maker or Tibco
* Familiarity with cloud computing based data-warehouses such as Snowflake or Redshift, and relational SQL databases
* Hands-on experience in deep learning and LVM for real-time monitoring and anomaly detection of time-series data and automated root cause analysis
* Experience in data visualization and real-time GUIs using Streamlit, Plotly, Spotfire, etc.
* Familiarity with feedback control algorithms, real-time communication protocols, industrial process historians, and industrial automation platforms such as Delta V and ASPEN
* Knowledge of Cell Culture, Fermentation and Vaccines Conjugation