Pfizer (501+ Employees, 9% 2 Yr Employee Growth Rate)

4% 1-Year Employee Growth Rate | 9% 2-Year Employee Growth Rate | LinkedIn | $0 Venture Funding

What Is Employee Growth Rate & Why Is It Important?

Senior Scientist: Process Modeling and 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.

 

Both remote and onsite arrangements are available.

 

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
  • Independent, self-motivated personality with excellent oral and written communication skills

 

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 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.
  • Familiarity with Pharmaceutical Industry and manufacturing unit operations.

 

Work Location Assignment: Flexible

 

 

Pfizer requires all U.S. new hires to be fully vaccinated for COVID-19 prior to the first date of employment.  As required by applicable law, Pfizer will consider requests for Reasonable Accommodations.

 

 

Sunshine Act

Pfizer reports payments and other transfers of value to health care providers as required by federal and state transparency laws and implementing regulations.  These laws and regulations require Pfizer to provide government agencies with information such as a health care provider’s name, address and the type of payments or other value received, generally for public disclosure.  Subject to further legal review and statutory or regulatory clarification, which Pfizer intends to pursue, reimbursement of recruiting expenses for licensed physicians may constitute a reportable transfer of value under the federal transparency law commonly known as the Sunshine Act.  Therefore, if you are a licensed physician who incurs recruiting expenses as a result of interviewing with Pfizer that we pay or reimburse, your name, address and the amount of payments made currently will be reported to the government.  If you have questions regarding this matter, please do not hesitate to contact your Talent Acquisition representative.

 

 

EEO & Employment Eligibility

Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status.  Pfizer also complies with all applicable national, state and local laws governing nondiscrimination in employment as well as work authorization and employment eligibility verification requirements of the Immigration and Nationality Act and IRCA.  Pfizer is an E-Verify employer.

 

 

Engineering

 

 

#LI-Remote #LI-PFE

Tagged as: 501+ Employees, Hide US-Only Jobs

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