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Lead, Machine Learning Research (Director)


This is a Full-time position in Vancouver, BC posted January 31, 2023.

Role Summary Pfizer’s Machine Learning Research department in our Worldwide Research, Development and Medical (WRDM) organization is seeking a passionate, creative, and experienced machine learning scientist to lead the development and implementation of cutting-edge machine learning tools to accelerate the most difficult drug discovery challenges.

The ideal candidate should have an outstanding scientific reputation in the field of machine learning research, be very familiar with the drug discovery processes, have a solid life science relevant domain knowledge and be passionate about visionary research strategies.

They will work in close collaboration with groups across Research Units to address challenging problems such as target discovery.

In addition, they will cover a broad range of research and development activities within Pfizer’s R&D and lead efforts to advance ML techniques at Pfizer by establishing collaborations with external institutions in academia and industrial labs.

This leader would thereby ensure that Pfizer’s internal capabilities are at the State-of-the-Art and are respected externally by experts in the field.

Role Responsibilities Develop innovative machine learning approaches that leverage the plethora of Pfizer’s proprietary data in conjunction with external data sources to advance drug target discovery and identify novel disease treatment mechanisms or biomarkers Establish a machine learning tech-stack to cope with, spurious correlation, obscuring variation and inherent multimodality of biomedical, clinical, and -omics data to support scientists in the Research Units with explainable predictions / insights on relevant endpoints Responsible for developing and implementing actionable strategic guidance to increase R&D productivity and efficiency using ML Being able to identify truly machine learnable projects, that have a clear business case with strong impact on the value chain, define concrete baseline metrics to track project progress, measure effective project execution and bring them to successful completion Leverage the full spectrum from traditional statistical modeling to deep learning algorithms to provide useful insights for all stakeholders in WRDM Build, scale, and deploy predictive models form large-scale scientific data from Medicinal Sciences, Integrative Biology, and Pfizer Digital Manage, mentor, and develop a team of 2-3 PhD-level Machine Learning scientists and/or post-doctoral fellows Remain current with respect to literature; proactively identify, assess, and internalize promising methods, tools, and external vendors Strengthen Pfizer’s external visibility and scientific reputation of excellence through contributing to open-source projects, publishing in relevant ML conferences and top journals, engaging with the scientific community and establishing new collaborations with leading academic and industrial research institutions Qualifications Formal training in Computer Science, Computational Biology, Computational Chemistry, Physics, Statistics, Applied Mathematics, related technical discipline, or relevant practical experience 10 years scientific programming experience and algorithm design related to machine learning methods Applied experience with contemporary ML algorithms in either of natural language processing, computer vision, and predictive modeling Working knowledge of one or more scientific data types (e.g.

biomedical images, biomedical text, large-scale, multidimensional ‘omics, clinical or Real World Data, etc.) Preferred Qualifications PhD, 9 years of relevant research experience with developing machine/deep learning-based solutions and a sincere interest for computational life sciences (statistical genetics / computational biology / clinical epidemiology).

Hands-on experience in handling, processing, integrating, and analyzing large heterogenous data sets related to industrial drug discovery research with of one or more scientific data types (e.g., biomedical images, large-scale multidimensional ‘omics, clinical or Real World Data, etc.) Highly creative person with outstanding problem-solving skills to tackle complex analysis tasks in a timely fashion Sound mathematical knowledge in representation learning, geometric deep learning, generative modeling, information theory, statistics and/or causal inference in combination with practical experience from the perspective of model selection and validation Strong publication record and demonstrated contributions to the field, e.g.


Solid expertise with ML libraries such as PyTorch, Lightning, TensorFlow, (JAX) is mandatory Programming skills in Python must be top notch.

Experience with relevant libraries of the Python scientific stack is a big plus.

Additional programming skills in R / Bioconductor is another big plus Familiarity with GPU computing both on-premises and on cloud platforms (AWS, Google Cloud, …) Passion and curiosity for data and proven ability to take ideas from prototype to production Strong interpersonal skills, empathic and effective leadership skills, excellent written and verbal communication, and the ability to clearly explain complex problems and their solutions to scientist outside the machine learning field We are an innovative and global team of scientists passionate about exploring how machine learning can advance drug discovery and development.

We are looking forward to meeting like-minded people Other Job Details Preferred Location: Cambridge, MA.

Additional Location Information: Groton, CT or La Jolla, CA.

Eligible for Relocation Package Eligible for Employee Referral Bonus Relocation assistance may be available based on business needs and/or eligibility.

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.

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