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Job Description
Key Responsibilities
Lead NLP Initiatives: Drive development and implementation of advanced NLP models to analyze unstructured text data related to clinical monitoring quality and risk management.
Build and Optimize Predictive Models: Apply machine learning techniques to identify patterns and trends with a focus on preventing/corrective actions for improving quality assurance practices.
Collaborate Across Teams: Partner with crossfunctional teams including other data science business and tech teams quality assurance and clinical operations to understand and solve critical business challenges.
Ensure Model Governance: Implement and monitor best practices for model governance accuracy and reliability in a highly regulated environment ensuring adherence to industry standards and regulatory requirements.
Data Preprocessing and Cleaning: Oversee data acquisition preprocessing and quality control of complex datasets working with structured and unstructured data in the R&D domain.
Lead Data Science Projects: Mentor and guide junior data scientists and analysts ensuring robust project management timely delivery and effective stakeholder communication.
Continuous Improvement: Identify opportunities to improve data workflows tooling and processes for enhanced productivity and reproducibility.
Research and Innovation: Stay abreast of industry trends and advancements in NLP machine learning and generative AI to drive innovation within the quality and risk management framework.
Performance Metrics and Reporting: Establish and track key performance indicators to assess model impact and value aligning outcomes with organizational quality and risk management goals.
Develop Gen AI Solutions: Explore and integrate generative AI models to innovate on complex language tasks such as summarization data synthesis and anomaly detection
Remote Work :
No
Full Time