Equity Research Analyst, AI Platform
About The Position
StockStory, part of CNBC, is building the next generation of AI-powered equity research for individual investors. We operate like a startup—small team, high ownership, fast decisions, and direct access to leadership—with the resources and long-term backing of a well-capitalized public company. Our mission is to help individual investors make better investment decisions by combining institutional-quality equity research, quantitative methods, proprietary data, and AI. This role is designed for investors who still want to apply and sharpen their fundamental research judgment, but who are more excited by building scalable systems than by repeating the same research process company by company, quarter after quarter. It is especially well suited to people who want to future-proof their investing career by learning how great equity analysis gets translated into software, models, and AI-enabled products. You will be instrumental to the team that builds and operates core components of our AI equity research engine: LLM workflows that convert unstructured information into structured signals, and factor models that turn those signals into consistent, scalable outputs for individual investors. You will be working on a small, high-caliber team that brings together top-tier engineering, product, and buy-side talent, including senior analysts with prior experience at firms such as Millennium, Point72, and KKR. Team members are expected to operate with a high degree of ownership and autonomy, contributing directly to core research, product, and modeling decisions while working closely with engineering and senior leadership in a highly collaborative, low-bureaucracy environment with direct access to decision-makers.
Requirements
- Minimum of 2 years of buy-side public markets investing experience (hedge fund, long-only fund, family office, or endowment), with a focus on long-term, fundamental analysis.
- Experience working with data. You will closely collaborate with the Engineering team to design and build automated equity analysis features blending LLM-based agentic and quantamental approaches, leveraging a modern and evolving technology stack that is being actively expanded
- Systemic, data driven thinker with the ability to productize fundamental research into a repeatable, systematic strategy and a desire to “build the machine that does the job”
- Experience contributing to long-term investment theses for a sector or single equity supported by qualitative and quantitative factors
- Ability to read financial statements, solid accounting knowledge, experience building three-statements models
Responsibilities
- Collaborate to convert equity research insights and conclusions into scalable AI equity research platform features that help individual investors with stock discovery, research, and selection
- Design and evaluate LLM-based workflows to process unstructured data, analyze it and translate it into structured metrics and factors
- Support the development and evaluation of performance of sector-based factor models using a combination of traditional fundamental research, statistical techniques, and quantitative factor design
- Conduct deep research and initiate coverage on public equities across industries
- Contribute to stock-picking models that surface the best opportunities to a large retail investor audience and produce structured reports supporting them
- Partner with Engineering to implement pipelines (APIs, DAGs, databases), establish reproducible backtests/evaluations, and ship analysis features/capabilities
Benefits
- Free onsite fitness center with state-of-the-art equipment, plus daily group classes
- Gourmet cafeteria with daily specials plus soup and salad bars
- Dry cleaning, shoe shining and sneak peeks
- Free shuttle transportation to and from multiple locations in Manhattan, Brooklyn, Hoboken and Jersey City
- Meaningful and continued investment in data, technology, and product development
- Opportunity to contribute to a growing team within CNBC that is expected to scale significantly over time
- Meaningful exposure to senior leadership
- Ability to influence how the platform evolves
- Bonus eligible
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
