Data scientist with GenAI

Data Scientist

The DCRS Inbound Correspondence Team is seeking a highly skilled Data Scientist to design, develop, and maintain document capture and intelligent processing solutions. This role combines machine learning, NLP, and emerging GenAI capabilities to transform large-scale structured and unstructured data into actionable insights and automated workflows. The ideal candidate brings a strong foundation in software engineering, hands-on experience building enterprise-scale ML/NLP solutions, and exposure to modern open-source Gen AI models. This individual will operate within an Agile environment, partnering across technology and business teams to deliver impactful solutions.

Key Responsibilities

• Design, build, and deploy machine learning and NLP models for document processing and correspondence analysis
• Develop and maintain end-to-end ML pipelines, including: data ingestion, cleansing, and transformation; feature engineering and model selection; performance tuning, evaluation, and visualization
• Implement GenAI-driven solutions for document understanding (e.g., summarization, classification, entity extraction)
• Build and optimize solutions leveraging OCR technologies for scanned and unstructured documents
• Develop scalable systems to process large volumes of structured and unstructured data
• Partner with cross-functional teams across Line of Business, Risk, and Technology to deliver solutions aligned with business needs
• Contribute to software engineering best practices, including CI/CD, testing, and production deployment
• Work within an Agile delivery model, supporting sprint planning, development, and release cycles

Required Qualifications

• 7+ years of experience as a Data Scientist or in a related role
• Bachelor's degree in computer science, Data Science, or a related technical field
• 5+ years of programming experience, with strong proficiency in Python for ML/NLP development
• Proven experience developing supervised and unsupervised ML models, including data analysis and feature engineering, model training, validation, and performance optimization, ensemble techniques, and evaluation metrics
• Hands-on experience building ML/NLP pipelines for large-scale datasets (structured & unstructured)
• 2+ years of experience developing enterprise ML/NLP solutions in one or more of the following: Named Entity Recognition (NER), Document Classification, Document Summarization, Topic Modeling, Sentiment Analysis, Dialog Systems
• Experience working with OCR technologies and document processing solutions
• Exposure to open-source GenAI models and frameworks (e.g., Hugging Face, LLaMA, Mistral, LangChain)

Salary Range: $100,000-$110,000 a year