Sr. AI Scientist - Life Sciences

Overview

Senior AI Scientist role at Abbott Cancer Diagnostics, largely self-driven and working on extremely complex projects that apply advanced AI and machine learning to biological, genomic, clinical and healthcare data in advanced cancer screening and precision oncology. The role combines hands-on work with technical and strategic leadership from ideation through deployment.

What you'll do

• Lead development of perspectives on technology "affordance": what advances in AI allow us to do more efficiently or effectively than before.
• Work with stakeholders to identify, refine, prioritize and formalize requirements for ML- and AI-based solutions to business problems, with a focus on bioinformatics, biostatistics and data engineering applications.
• Collaborate with other ML/AI engineers and relevant partners to provide technical and strategic leadership for designing software solutions that use state-of-the-art AI and machine learning techniques.
• Work with AI, ML and software engineers to lead the implementation and deployment of ML and AI solutions, complemented by hands-on work and clear deliverables.
• Provide leadership in developing an AI strategy that empowers the team to leverage existing and in-house AI and ML tools to accelerate and enhance bioinformatics, biostatistics and data science processes and outcomes.
• Lead internal initiatives to build training resources, develop knowledge bases, and educate on advanced AI and ML technologies and best practices.
• Solve complex problems using sophisticated analytical thought to exercise judgement and identify innovative solutions.
• Provide mentorship and coaching to more junior team members.
• Act as resource and subject matter expert in core team and cross-functional meetings.
• Contribute to the intellectual property portfolio by implementing innovative and creative ideas to solve problems or improve current methods.
• Exercise discretion and judgment within broadly defined practices and policies in selecting methods, techniques and evaluation criteria for obtaining and interpreting results.
• Communicate effectively, influence decision-making, and explain difficult, sensitive or highly complex information to peers.
• Uphold company mission and values through accountability, innovation, integrity, quality and teamwork, and support and comply with the company's Quality Management System policies and procedures.

What you'll need

• Ph.D in Statistics, Computational Biology, Computer Science, or related quantitative field as outlined in the essential duties, OR Master's Degree in Statistics, Computational Biology, Computer Science, or related quantitative field as outlined in the essential duties plus 4 years of relevant experience.
• 5+ years of experience in statistics, computational biology, applied mathematics, or related quantitative field as outlined in the essential duties.
• 5+ years of experience with artificial intelligence and machine learning algorithms.
• Demonstrated experience with and mastery of advanced AI concepts, such as artificial neural networks, deep learning, and model architectures.
• Demonstrated experience with and mastery of AI and machine learning techniques within one or more of: natural language processing, image processing and computer vision, image and pattern recognition.
• Demonstrated experience with and mastery of large language models for generative AI and associated concepts, such as transformer architecture and retrieval augmented generation.
• Strong programming ability with demonstrated experience in Python and common machine learning libraries such as PyTorch and MLFlow.
• Knowledge and experience working with open-source AI models.
• Excellent communication skills and the ability to explain complex topics to audiences of varied backgrounds.
• Demonstrated ability to perform the essential duties of the position with or without accommodation.
• Authorization to work in the United States without sponsorship.

Nice to have

• 8+ years of life sciences industry experience working with biological data.
• 8+ years of industry experience in molecular diagnostics, preferably cancer diagnostics.
• Expertise in data mining approaches within healthcare settings, generating insight from routinely collected healthcare data.
• Basic knowledge of ML-Ops and processes for managing the versioning and deployment of machine learning models.
• Scientific understanding of cancer biology.
• Basic knowledge of cloud computing, particularly AWS SageMaker and HyperPod.

Details

• Location: United States of America, Remote.
• Base pay: $99,300.00 – $198,700.00; pay may vary by specific location.
• Division: ONCO Cancer Diagnostics. Job family: Product Development.
• Work shift: Standard.
• Travel: 5% of the time, may include overnight and weekend travel.
• Ability to work on a computer or mobile device for approximately 85% of the working day, with continuous sitting for prolonged periods and keyboard use of 50% or more of the workday.
• Ability to work designated schedule and maintain regular and reliable attendance.