Senior Data Scientist I

Data Scientist

AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio.

At AbbVie, Preclinical Safety (PCS) is responsible for creating and executing development plans that support novel drug candidates from nonclinical testing through first-in-human, registration, and post-marketing phases. The Digital and Computational Pathology Laboratory in PCS is seeking a talented and motivated Data Scientist to develop cutting-edge methodologies in computer vision and AI to power whole slide image analyses in nonclinical drug development. The ideal candidate will possess a strong background in computer science, engineering, or a related field, with emphasis on computer vision and deep learning.

The role involves designing and implementing algorithms for anomaly detection, segmentation, and classification to contribute to the development of accurate and efficient AI-assisted digital pathology readouts. Specific skills required include proficiency in programming languages such as Python and C++, as well as experience with machine learning frameworks like TensorFlow or PyTorch. Familiarity with image processing libraries and a solid grasp of deep learning models, including large vision models, are essential. Additionally, experience in curating and analyzing large-scale biomedical datasets is highly desirable. The candidate should have strong analytical skills, a track record of publication in high-impact journals, and an ability to work collaboratively within a multidisciplinary team.

Responsibilities:

• Conceive, design and implement original technical ideas that solve significant scientific or business problems through the integration, visualization, and analysis of large and complex data, especially biomedical images. Routinely demonstrate initiative and creativity in developing technology solutions.
• Demonstrate high proficiency across a wide range of technologies related to the storage, transfer, integration, visualization, and analysis of large and diverse data sets. Expertise in software development, data warehousing, statistics, and AI/ML.
• Demonstrate deep knowledge of biomedical research and the pharmaceutical business, and utilize this knowledge in the rapid advancement of agile, impactful, and cost-effective solutions.
• Highly autonomous and productive in performing activities, requiring only minimal direction from or interaction with supervisor.
• Initiate new areas of investigation that are meaningful, reliable, and may be incorporated directly into a scientific or business activity.
• Direct mentorship of others.
• A primary author of publications and presentations; present at external scientific conferences.
• Understand and adhere to corporate standards regarding applicable Corporate and Divisional Policies, including code of conduct, safety, GxP compliance, and data security.

Qualifications:

• Bachelor's Degree and typically 10 years of experience, OR Master's Degree and typically 8 years of experience, OR PhD in computer science, biomedical engineering, pathology informatics, or a related field, with emphasis on computer vision and machine learning and no experience necessary.
• Record of scientific initiative and creativity in research or development activities.
• Capable of independently designing and executing experiments, interpreting data, and identifying appropriate follow-up strategies.
• Excellent project management skills; ability to multitask and work within timelines.
• Ability to resolve key project hurdles and assumptions by effectively utilizing available information and technical expertise.
• Demonstrated scientific writing skills.
• Global mindset to thrive in a diverse culture and environment.
• Excellent oral and written English communication skills.

Preferred:

• Research experience with unsupervised and weakly supervised CNN and RNN architectures such as GANs, contrastive learning, multiple instance learning, and transformer models.
• Subject matter expertise in foundation model(s).
• Familiarity with commercially available digital pathology software (e.g., Visiopharm, HALO, Patholytix).
• Knowledge regarding machine learning operations (MLOps) principles.

Key Leadership Competencies:

• Builds strong relationships with peers and cross functionally with partners outside of team to enable higher performance
• Learns fast, grasps the "essence" and can change course quickly where indicated
• Raises the bar and is never satisfied with the status quo
• Creates a learning environment; open to experimentation and suggestions for improvement
• Embraces the ideas of others, nurtures innovation, and manages to reality

Additional Information:

• The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future.
• We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.
• This job is eligible to participate in our short-term incentive programs.

AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community. Equal Opportunity Employer/Veterans/Disabled.

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Pay Range: $96500 - 183500 USD

Where We Work:

Role is exclusively performed at a site or office and onsite presence is required. Employees who are site/office-based and can occasionally perform their role virtually work both in the office and remotely*, following the policies and regulations in place at their location. US Employees must be in the office on Tuesday, Wednesday, and Thursday with flexibility to work remotely on Mondays and Fridays. Three days in the office is the minimum; some individuals or teams may require more in-office days due to meetings, business/project needs or their role.