Data Scientist - Generative AI Applications

at  Stefanini Inc

OVERVIEW:

• We are seeking an experienced Data Scientist to join our team, focusing on the development and deployment of Generative AI (GenAI) solutions in a commercial business setting. This role involves working with advanced technologies, including vector databases, Retrieval-Augmented Generation (RAG) approaches, and building end-to-end AI pipelines to deliver actionable insights and solutions to business challenges.

QUALIFICATIONS:

• Master’s or Ph.D. in Computer Science, Data Science, Machine Learning, or a related field.
• Proven experience in developing and deploying Generative AI models in business settings.
• Strong programming skills in Python, R, or similar languages.
• Experience with data manipulation and analysis using tools like SQL, Pandas, and NumPy.
• Solid understanding of statistical analysis and data visualization techniques.
• Excellent problem-solving skills and the ability to work independently and collaboratively.
• Strong communication skills with the ability to explain complex technical concepts to non-technical stakeholders.

Preferred Qualifications:

• Experience with natural language processing (NLP) and computer vision applications.
• Familiarity with cloud platforms such as Azure.
• Experience in project management and leading data science initiatives.

• Model Development: Design, develop, and optimize RAG (Retrieval-Augmented Generation) models to facilitate effective information retrieval and generation aimed at solving complex business problems and enhancing the decision-making process.
• Vector Database Management: Utilize vector databases and advanced indexing techniques to efficiently store and retrieve relevant information for conversational contexts.
• LLM Fine-Tuning: Fine-tune and optimize large language models (LLMs).
• NLP Techniques: Implement and experiment with cutting-edge NLP and similar techniques to enhance the capabilities and performance of our AI products.
• Collaborate with cross-functional teams, including business units and platform/software engineers, to identify opportunities for integrating Generative AI models into production systems, ensuring scalability, reliability, and performance.
• Stay up-to-date with the latest advancements in Generative AI and data science technologies.
• Communicate findings and recommendations to stakeholders through clear and concise reports and presentations.