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This is a role that'll offer you the opportunity to build an in-depth knowledge of implementing AI solutions around documents and NLP in a financial services environment.
Job Responsibility:
Research and build knowledge in the forefront of AI
Build & maintain a roadmap of AI capabilities from inception to production
Guide data science team to perform their work and growth
Work with product and software development teams from requirements to production
Design, develop, test, support and maintain AI development
Requirements:
4+ years of experience in Data Science or NLP, ideally with exposure to unstructured data and document understanding use cases
Hands-on experience building or contributing to solutions involving Generative AI, such as information extraction, summarization, or document classification
Working knowledge of LLMs (e.g., OpenAI, Claude, Mistral) and frameworks like LangChain or LLM orchestration tools – or a strong willingness to learn them quickly
Proficiency in Python, with familiarity in libraries such as Pandas, NumPy, Scikit-learn, and either PyTorch or TensorFlow
Basic understanding of prompt engineering, embedding models, and use of vector databases (e.g., FAISS or Chroma)
Familiarity with REST APIs, scripting, and integration with external systems – experience is a plus
Some exposure to the Model Risk Management (MRM) process, or an interest in learning how to align data science work with compliance, validation, and documentation standards
Comfortable working with PDFs, OCR tools, and document parsing frameworks (e.g., PyMuPDF, Tesseract)
Experience using version control systems (Git) and working in collaborative development environments
Strong communication skills and ability to collaborate with product managers, engineers, and business stakeholders
Motivated to grow in the GenAI space, stay up to date on emerging tools and techniques, and contribute to innovation and delivery
Excellent communication and collaboration skills, with the ability to interact effectively with technical and non-technical stakeholders
Bachelor’s degree in a relevant field preferred (e.g., Data Management, Computer Science, Information Systems)
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