Top Tech Jobs & Startup Jobs in Boston, MA

Apply advanced AI, ML, and computational modeling to drug discovery and early development. Build scalable data pipelines and predictive models, integrate diverse scientific datasets, ensure model validation and reproducibility, and communicate insights to multidisciplinary teams to support decision-making.

Lead development and deployment of hybrid ML and mechanistic modelling pipelines (PK/PD, QSP) to generate actionable insights across drug discovery and development. Drive reproducible workflows, integrate diverse datasets, advance AI-augmented modelling, and communicate results to influence translational decision-making.

The Director & Group Head of Applied AI will lead AI strategy in drug discovery, collaborating with teams to deploy machine learning solutions and drive innovation in biomedical research.

Lead the Oncology Data Science team in developing data-driven solutions for low molecular weight drug development, leveraging AI and machine learning. Collaborate with stakeholders to execute data science strategies and ensure adherence to best practices in analytics.

Lead enterprise applied AI strategy and a distributed team to design, deploy, and scale generative AI and agentic solutions. Drive solution architecture, integrations, MLOps/LLMOps, reusable services, governance, and cross-functional adoption while measuring business impact and modernizing systems for production use.

Lead Clinical Data Engineering for oncology research, overseeing data infrastructure, analytics, team management, and regulatory compliance while fostering partnerships.

Apply deep learning and generative AI to digital pathology and spatial biology datasets to develop image-analysis algorithms, biomarkers, segmentation, cell phenotyping, and spatial feature extraction. Collaborate with pathologists and translational teams, validate and benchmark methods, publish results, and present at scientific forums to support oncology drug discovery.

Lead MarTech product management maturity, governance, and operations across a complex portfolio. Establish scalable frameworks, KPIs, and dashboards; drive prioritization, planning, budgeting, and cross-functional alignment; partner with IT, marketing, vendors, and executives; and lead change initiatives including AI-enabled capabilities to improve delivery and ROI.

The Director, Analytics Infrastructure & Pipeline Operations is responsible for creating automated data pipelines and centralized feature stores for data science, leveraging AI technologies to optimize workflows and ensure data quality.

The Director, Analytics Standards & Impact Measurement oversees AI/ML standards, quantifies analytics impact, and ensures compliance within commercial analytics initiatives.