Role Overview
This unique role places you in the intersection of data science, financial modeling, data engineering, LLM application, and institutional sales. You will lead data-oriented projects from conception to implementation, all while supporting our institutional sales team in delivering and explaining our data & models to clients. You’ll work with other data pipeline engineers and alongside our CTO to architect data ingestion and automatic QA processes for new data sources relevant for Caplight’s Data product. You will have regular collaborating with the co-founders of Caplight and have a strong voice in the company’s data strategy.
About Caplight:
Caplight is a seed-stage fintech company based in San Francisco building the future of the private markets. We operate a best-in-class data and trading platform for private tech company stock. Our vision is to make private market trading as easy as public stock trading. The customers we serve are many of the world's top banks, VCs, hedge funds, and other institutional asset managers. Our team is a small group of dedicated builders, and we pride ourselves on the quality and pace of our work. We’re excited for you to join the team!
Role Responsibilities
- Build and maintain pricing models: Create and fine-tune pricing models for illiquid assets, such as Caplight’s MarketPrice that predicts a daily price for actively-traded private companies
- Identify and implement new model features: Creatively identify potential new features/signals, analyze them for their impact, and incorporate them into ML models
- Data engineering: Architect and build data pipelines to collect, parse, and store data used in ML pipelines and otherwise displayed on the Caplight Data platform.
- LLM Implementation: Experiment with and implement LLMs to automate parts of Caplight’s data ingestion pipeline and support new features on the Caplight platform
- Sales Support: Join calls with top-tier financial firms to explain Caplight’s models, data collection strategies, and help sell subscriptions.
- Data Analysis Client Deliverables: Respond to client requests for data analysis or data outputs, typically with a 24-hour turnaround time
- Improve data pipeline efficiency: Optimize our data ingestion pipeline and our data QA processes to improve scale and reduce manual human review of data.
About you:
- 🌉Located in the SF Bay Area and eager to work in-person in SF at least 3 days per week (531 Howard St)
- 🧑💻 At least 6 years of professional experience in a data engineering, data science, or financial quant position(s). Strong proficiency with Python, R, Postgres, and LangChain. Ideally, some experience with Typescript, NodeJS, and Google Firebase.
- 📈 At least 2 years of experience conceptualizing and implementing ML models from scratch using Bayesian modeling, LLMs, and linear regression