LLM Analyst

Bayview Asset ManagementCoral Gables, FL
8dHybrid

About The Position

The Research Team at Bayview works with businesses across the firm, including portfolio managers, traders and Lakeview, a mortgage servicing/origination business. Our team is dedicated to delivering cutting-edge solutions through rigorous research and advanced modeling techniques. We oversee the data analysis process from start to finish: Data engineering: fetch, explore, and clean the data Research: analyze data with quantitative rigor to answer the business question at hand Modeling: identify the best statistical methods to apply to a given problem Development: code up the implementation with consideration for efficiency and extensibility The Research team at Bayview Asset Management is hiring an LLM Analyst to unlock insight from large volumes of textual data, both external and internal, to inform investment theses, improve operations, and answer foundational questions about the mortgage industry and more broadly, the economy.

Requirements

  • Bachelor's or master's degree in mathematics, statistics, physics, computer science, or another quantitative field. Degree in the social sciences/humanities with demonstrated analytical work is also welcome.
  • No prior job experience is required, but experience conducting in-depth research with real-world data is required (textual data preferred)
  • Proficiency in a programming language (e.g. Python)
  • Excellent reading, writing and communication skills
  • Strong analytical and problem-solving skills with interest in understanding the business

Responsibilities

  • Engage with the business: Meet with portfolio managers, traders, marketing and servicing teams to identify and narrow down the question. Understand the business context behind each question.
  • Think critically and creatively: Determine the best tool to answer the question at hand. Be able to think critically and creatively about what to try. AI or LLM will not always be the answer.
  • Prototype quickly but evaluate rigorously: Design prompts, run experiments in notebooks and concisely synthesize results for fast iteration. Define clear success metrics to measure progress.
  • Communicate clearly: Produce narrative summaries of findings and “so-what” recommendations for non-technical stakeholders.
  • Be comfortable with imperfect data: Be familiar with basic data exploration and manipulation techniques. Work with the source to identify root issues in the data
  • Operate responsibly and with integrity within Bayview governance; adhere to privacy/PII handling and model-risk standards.
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