GenAI Senior Data Scientist

 As a Senior Data Scientist, you will collaborate with the Data Science and Machine Learning team and will create data science, machine learning, and AI solutions to better address the needs of our constituents (students, alumni, faculty, researchers, staff, and community at large).
You will experiment with everything from the latest AI algorithms and techniques to blended and immersive environments, multi-modal and varied-form content, and the most innovative research and teaching methodologies.
You will be highly influential in advancing our LLM applications and guide teams towards impactful and ethical AI. We seek an expert who is eager to grow and disseminate GenAI model expertise across the organization.
In this role, you will translate the needs of our cross-functional stakeholders into user-facing applications that leverage NLP techniques and large language models (LLMs).

As a Sr. Data Scientist on our GenAI applications team, you will work on products like conversational search interfaces, chatbots, text summarizers, recommender engines, and more based on the needs of the constituents.

You will partner with Product Managers, Machine Learning Engineers, Cloud Platform Engineers, and cross-functional partners to develop production-grade algorithms

Duties and Responsibilities:
• Architect the overall framework and infrastructure for GenAI products like search interfaces, bots, summarizers, etc. Develop and implement techniques to optimize model performance to meet specific product goals
• Collaborate closely with product management and engineering leads to align on technical roadmap. Guide engineering teams to effectively leverage LLM capabilities in product implementations
• Establish protocols and systems for building fair, accountable and transparent LLM[1]based applications. Lead efforts to proactively assess and mitigate risks due to model biases or failures • Implement robust feedback pipelines, monitoring and corrections to ensure model safety
• Design and oversee curation of high-quality datasets tailored for LLM training for each product. Build data science pipelines from feature generation, data visualization and models evaluation; design the solution, build initial code and provide documentation with ways of working to maximize time to value and re-usability.
• Communicate clearly and effectively to technical and non-technical audiences, verbally and visually, to create understanding, engagement, and buy-in. Contribute novel research and analyses to leading academic conferences and journals.