Associate Scientific Director, Data Science
Millipore Corporation

Billerica, Massachusetts


Work Location: Billerica, Massachusetts
Shift:
Department: HC-RD-BSB Bioinformatics
Recruiter: Rena Ann Peterson

This information is for internals only. Please do not share outside of the organization.

Your role:

You will work with scientists and clinicians, primarily across our neurology and immunology therapeutic areas, applying machine learning and AI techniques to many of the most pressing problems in drug development. You will be part of a data sciences team that uses molecular, medical, and literature datasets to

  • match drugs to the patients who most need them
  • elucidate drugs' mechanism of action
  • identify biomarkers for response and safety
  • refine clinical trial designs
  • discover or prioritize candidate drug targets
In your projects, you will work across datatypes and settings: collections of >10^6 single cells, MRI images, the biomedical literature, or large real-world datasets (eg, insurance claims, electronic healthcare records). You will work with the biologists, clinicians, biomarker specialists, and other non-computational scientists as well as other data scientists.

Who You Are:

You have a background in computer science or data science and a track record of project work and publications that show you know how to apply AI and ML techniques to a variety of scientific problems. Your experience demonstrates an understanding of the underlying math, common tools, good implementation practices and engineering skills, knowledge of relevant biological and medical data types, and the business sense to connect your skills to others' needs. You have experience with data from multiple areas, ideally in the healthcare domain (for example, image recognition or processing; natural language processing; EHRs, insurance claims, or other medical datasets; or single-cell datasets) but possibly in other business areas.

Minimum Qualifications:
  • Master's degree in computer science or related field
  • Minimum 6 years relevant experience
  • Exceptional record applying ML and AI techniques to scientific problems reflecting substantial experience with at least one major area of AI/ML such as deep neural networks, LLMs, embeddings, transformers, GCNs, auto-encoders, etc. Experience with hyperparameter tuning and methods to ensure model generalization.
  • Strong experience with Python and R ecosystems for machine learning (including several ML libraries) and reproducible research
  • Strong hands-on experience using scalable computing techniques in a high-performance computing environment to overcome performance limitations and challenges from large datasets
  • Experience with one or more big data environments or tech stacks

Preferred Qualifications:
  • PhD in computer science, data science, machine learning, or related field
  • Experience in pharma or biotech
  • Full stack experience with one or more ML environments or tools - ability to take over for data engineering or ML ops as needed.
  • Experience with statistics and non-ML data analyses
Location: Position can be remote. Prefer someone in the Boston area.

The Company is an Equal Employment Opportunity employer. No employee or applicant for employment will be discriminated against on the basis of race, color, religion, age, sex, sexual orientation, national origin, ancestry, disability, military or veteran status, genetic information, gender identity, transgender status, marital status, or any other classification protected by applicable federal, state, or local law. This policy of Equal Employment Opportunity applies to all policies and programs relating to recruitment and hiring, promotion, compensation, benefits, discipline, termination, and all other terms and conditions of employment. Any applicant or employee who believes they have been discriminated against by the Company or anyone acting on behalf of the Company must report any concerns to their Human Resources Business Partner, Legal, or Compliance immediately. The Company will not retaliate against any individual because they made a good faith report of discrimination.



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