Data Scientist Lead

As Data Scientist Lead within Commercial & Investment Bank with the Healthcare Provider team, you will lead a team in building advanced solutions for image classification, text categorization, and intelligent data extraction from scanned documents.

You will have deep proficiency in Python, PyTorch, TensorFlow, Hugging Face Transformers, AWS SageMaker/Bedrock, and hands-on experience with CNN/transformer architectures, OCR technologies, and multimodal document understanding models.

This role involves managing the full ML lifecycle, from prototyping to production deployment on AWS EKS.

Job responsibilities


* Lead and mentor a team of data scientists in designing and executing advanced analytics and modeling projects focused on image classification, text categorization, and intelligent data extraction from scanned document images.

Foster a culture of curiosity, analytical rigor, and continuous learning by developing team members in deep learning, computer vision, NLP, and document AI techniques.


* Define and drive the analytical strategy for document understanding use cases, identifying the optimal combination of computer vision, NLP, and multimodal approaches.


* Build and fine-tune multimodal document understanding and text categorization models.

Leverage the interplay of textual content, spatial layout, and visual features to extract structured fields and key-value pairs from complex scanned documents, while enabling automated categorization, routing, metadata tagging, and entity extraction.


* Design rigorous experimentation and data quality frameworks, including A/B testing, cross-validation strategies, and statistical significance testing to evaluate model performance and hyperparameter tuning.

Establish best practices for annotation quality management, training data curation, active learning strategies, and ground truth validation to ensure high-quality labeled datasets.


* Design, manage, and optimize the workflows involved in preparing data for machine learning model training, select statistical or Deep Learning models that are best positioned to achieve business results.


* Develop and deploy models using Python and AWS SageMaker, managing the full lifecycle from exploratory data analysis and prototyping through production deployment, monitoring, and performance tracking.

Collaborate with data engineers and ML engineers to ensure seamless integration of analytical models into production document processing pipelines and data workflows.

Required qualifications, capabilities, and skills


* Bachelor's degree or MS or PhD in quantitative discipline, e.g.

Computer Science, Mathematics, Operations Research, Data Science.


* 7+ years of experience in data science or quantitative analytics, with at least 2+ years of experience in document AI, computer vision, or NLP domains.


* Strong foundation in statistics, mathematics, and programming, including probability, mathematical modeling, and experimental des...