GenAI Senior Data Scientist - 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 multimodal and variedform 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 crossfunctional stakeholders into userfacing 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 crossfunctional partners to develop productiongrade 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 LLM1based 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 highquality 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 reusability.

Communicate clearly and effectively to technical and nontechnical audiences verbally and visually to create understanding engagement and buyin. Contribute novel research and analyses to leading academic conferences and journals.

Identify trends and opportunities to drive innovation both in what we do and how we do it; evaluate new data science machine learning and AI technologies and tools that can boost team performance innovation and business value. Proactively analyze latest developments in large language models to deeply understand model capabilities limitations and best practices. Develop techniques to continually improve language understanding and model training

Mentor and develop junior data scientists in stateoftheart GenAI methods

Set technical vision and lead initiatives to accelerate product impact through cutting1edge LLM innovations

Complete other responsibilities as assigned.

Required Skills and Qualifications:

Minimum of nine years postsecondary education or relevant work experience

Advanced degree in mathematics physics computer science engineering statistics or an equivalent technical discipline desired

Minimum of three years experience in developing machine learning models with a track record of creating meaningful business impact and working with multiple stakeholders.

Minimum of five years experience with Python.

Minimum of three years experience building production NLP and deep learning models using PyTorch/Tensorflow along with using large language model architectures (BERT GPT3 etc.)

Experience building advanced workflows such as retrieval augmented generation model chaining dynamic prompting PEFT/SFT etc. using Langchain and similar tools

Experience establishing model guardrails and developing bias detection and mitigation techniques for AI applications

Proficiency with various prompting techniques with a clear understanding of tradeoffs between prompting and finetuning

Experience with finetuning embedding models and tuning vector databases to improve performance of semantic search and retrieval systems

Deep understanding of underlying fundamentals such as Transformers SelfAttention mechanisms that form the theoretical foundation of LLMs

Experience with cloud computing platforms and tools (AWS)