Senior Scientist: Process Modelling and Interpretable Machine Learning

Found in: beBee jobs IE - 2 weeks ago

Dublin, Dublin City, Ireland Cpl Full time
Cpl in partnership with our client Pfizer Grange Castle are currently recruiting for a

Senior Scientist: Process Modelling and Interpretable Machine Learning

The Manufacturing Intelligence (MI) team within Pfizer's Global Technology & Engineering (GT&E) is responsible for driving the development and implementation of advanced analytics including AI/ML, soft sensor, advanced process control, and process condition monitoring solutions in support of manufacturing and future capabilities in Pfizer Global Supply (PGS).

As a member of MI, this role will have the opportunity to 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 for pharmaceutical manufacturing and quality operations.

Responsibilities

  • Technical contribution 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), and 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

  • A PhD degree in relevant engineering major, mathematics, or computer science is preferred.
  • Expert-level knowledge in Python is a must. Experience in any of the following languages is a plus: R, Matlab, JavaScript.
  • Ability to perform data engineering on real world big-data ranging from structured time-series datasets with thousands of features, to unstructured image, text, audio and video 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
  • Independent, self-motivated personality with excellent oral and written communication skills

Preferred Qualifications

  • Expertise in first principles (thermodynamics, reaction modelling, heat transfer, mass transfer principles), hybrid modelling. Ability to develop practical process models for real-time applications is a strong plus.
  • Experience in cloud-based code development and deployment environments such as AWS SageMaker 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 DeltaV and ASPEN.
  • Knowledge of Cell Culture, Fermentation and Vaccines Conjugation
  • Work Location Assignment: Hybrid, Flexible -dealing with USA

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