Principal Data Scientist, Data and AI Convergence
AbbVie
August 20, 2026
Remote friendly (North Chicago, IL)
United States
$141,500 - $268,500 USD yearly
IT
Responsibilities:
- Identify and assess enterprise gaps in R&D data convergence, analytics, and AI/ML integration; design scalable, integrated solutions.
- Architect cross-functional frameworks to integrate AI/ML into R&D and clinical workflows; ensure extensibility, maintainability, and alignment with enterprise data strategies.
- Lead production-grade AI/ML workflow orchestrations across data ingestion, feature engineering, model training, deployment, monitoring, and improvement.
- Apply advanced AI/ML (deep learning, NLP, generative AI) to improve R&D innovation/efficiency, clinical trial optimization, and portfolio decisions.
- Establish best practices, standards, and governance for enterprise AI/ML workflow integration (consistency, quality, regulatory compliance).
- Build reusable AI/ML components/templates and define metrics to monitor impact on efficiency and decision quality.
Qualifications:
- PhD (CS, Statistics, Bioinformatics, Computational Biology, Applied Mathematics, Data Science, or related) strongly preferred; Master’s considered with exceptional expertise.
- 4–5+ years scaling advanced AI/ML in enterprise environments; enterprise-wide workflow leadership with measurable impact.
- 5+ years in highly matrixed, complex environments; consulting in regulated pharma/biotech/healthcare preferred.
Technical Skills:
- Expert ML/AI (deep learning, neural nets, ensembles, transfer learning, generative AI).
- Proficiency with TensorFlow/PyTorch/Scikit-learn/Hugging Face; Python & R; CI/CD, testing, version control.
- MLOps and orchestration (Airflow, Kubeflow, MLflow), cloud (AWS/Azure), distributed computing, data integration, enterprise analytics platforms.
Benefits (if applicable per posting):
- Paid time off; medical/dental/vision insurance; 401(k); long-term incentive program eligibility.
- Identify and assess enterprise gaps in R&D data convergence, analytics, and AI/ML integration; design scalable, integrated solutions.
- Architect cross-functional frameworks to integrate AI/ML into R&D and clinical workflows; ensure extensibility, maintainability, and alignment with enterprise data strategies.
- Lead production-grade AI/ML workflow orchestrations across data ingestion, feature engineering, model training, deployment, monitoring, and improvement.
- Apply advanced AI/ML (deep learning, NLP, generative AI) to improve R&D innovation/efficiency, clinical trial optimization, and portfolio decisions.
- Establish best practices, standards, and governance for enterprise AI/ML workflow integration (consistency, quality, regulatory compliance).
- Build reusable AI/ML components/templates and define metrics to monitor impact on efficiency and decision quality.
Qualifications:
- PhD (CS, Statistics, Bioinformatics, Computational Biology, Applied Mathematics, Data Science, or related) strongly preferred; Master’s considered with exceptional expertise.
- 4–5+ years scaling advanced AI/ML in enterprise environments; enterprise-wide workflow leadership with measurable impact.
- 5+ years in highly matrixed, complex environments; consulting in regulated pharma/biotech/healthcare preferred.
Technical Skills:
- Expert ML/AI (deep learning, neural nets, ensembles, transfer learning, generative AI).
- Proficiency with TensorFlow/PyTorch/Scikit-learn/Hugging Face; Python & R; CI/CD, testing, version control.
- MLOps and orchestration (Airflow, Kubeflow, MLflow), cloud (AWS/Azure), distributed computing, data integration, enterprise analytics platforms.
Benefits (if applicable per posting):
- Paid time off; medical/dental/vision insurance; 401(k); long-term incentive program eligibility.