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Senior Scientist 1 - Machine Learning and Cheminformatics

Primary Chicago, Illinois Secondary Job ID 2210473 Categorie Information Technology Afdeling AbbVie

Senior Scientist I – Machine Learning/Cheminformatics

Here is an opportunity to work with the best of the best at the intersection of machine learning, deep learning, cheminformatics, and drug discovery to make a remarkable pan-abbvie impact by enabling people to lead longer and healthier lives.  As a Senior Machine Learning Scientist, you will work as part of AbbVie’s Information Research RAIDERS: Pharma Discovery team in conjunction with our partners across early as well as late drug Discovery and Developmental Sciences departments.  You will bring together the power of domain science and technology at the interface of cheminformatics, data engineering, and machine learning techniques to generate new understanding of the drug discovery process that contributes to finding faster and better drug discovery pipeline.  In this opportunity you will work as part of a highly capable team helping to bridge together domain specialists in medicinal chemistry, drug modelers, cheminformatics, and Developmental Scientists along with machine and deep learning scientist to extract insights from diverse data.  You will apply your established technical skills and experience with machine and deep learning techniques to deliver solutions capable of providing true insights that push forward the fundamental understanding of drug discovery process.  You will utilize your notable consulting mindset to bridge the communication gaps between domain scientists and technologists.  You will bring your solution architecture expertise to help design, develop, and deliver models and tools that extract and generate these insights. Come join us to help discover the next new drug discovery pipeline and help save lives.

Job Responsibilities

  • Define and support data transformation and preparation activities independently and in conjunction with data scientists.
  • Hands on, design and deploy models and solutions built around deep and machine learning technologies in conjunction with medicinal Chemists and deep learning engineers/scientists.
  • Hands on, design and deploy models and solutions built around compound and chemical reaction data and cheminformatics in conjunction with AbbVie domain scientists and experts.
  • Advise on, design and develop server-side programming components to support the delivery of solutions built on deep and machine learning models in conjunction with discovery and dev sci. scientists.
  • Research, evaluate, and recommend process improvements, including automated systems and enhanced models in support of activities.
  • Participate in a broader federated team of AI and automation specialists across AbbVie as part of the Information Research RAIDERS team, sharing expertise and educating a broader audience about solutions in your specialty.

Requirements

  • Additional degrees or education in cheminformatics, chemistry, pharmaceutical sciences, or other life sciences domain is preferred.

Minimum Experience:

  • Expertise with developing, implementing and deploying programs and computational solutions employing Machine Learning/Deep learning and Cheminformatics techniques
  • Proficiency in Python, SQL, and AWS/cloud computing capabilities and tools
  • Experience with pytorch, tensorflow, or similar ML framework
  • Experience with solution architecture development and deployment
  • Experience with chemistry, cheminformatics, and molecular data and testing procedures
  • Practical experience in a scientific discipline such as cheminformatics, pharmacology or related, ideally a BS or related degree

Skills:

  • Ability to work in an agile, fast-paced environment
  • Passion for exploratory projects, including proof-of-concept and proof-of-value engagements, and an ability to guide those concepts into production solutions
  • Ability to handle multiple projects at once
  • Ability to communicate effectively with multiple groups within the organization and effectively collaborate with external partners.
Significant Work Activities: Continuous sitting for prolonged periods (more than 2 consecutive hours in an 8 hour day)
Travel: No
Job Type: Experienced
Schedule: Full-time
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