Sr. Eq Research Analyst, AI Platform

Versant•Englewood Cliffs, NJ

4h•$200,000 - $235,000•Onsite

About The Position

VERSANT is an independent, publicly traded company that brings together powerhouse brands such as CNBC, MS NOW (formerly MSNBC), USA Network, Oxygen, E!, SYFY, and Golf Channel along with dynamic digital and direct-to-consumer brands such as Fandango, Rotten Tomatoes, GolfNow, GolfPass, and SportsEngine. StockStory, a newly acquired part of CNBC, is building the next generation of AI-powered equity research for individual investors. The team operates like a startup: small team, high ownership, fast decisions, direct access to leadership, and a culture focused on building rather than managing. It has the backing of a large, well-capitalized public company with iconic brands, meaningful free cash flow, and a long-term commitment to investing in data, technology, and the team. The mission is to help millions of investors achieve better results in the markets. This role is an opportunity to work at the intersection of investing, AI, and product, alongside exceptional engineers and investors, to define modern equity research. The company is looking for a highly driven and intellectually curious equity analyst to join the team to build a new generation of AI-powered equity research. This role is designed for investors who want to apply and sharpen their fundamental research judgment, and are excited by building scalable systems rather than repeating the same research process. It is well suited for individuals who want to future-proof their investing career by learning how equity analysis translates into software, models, and AI-enabled products. The analyst will build and operate core components of the AI equity research engine, including LLM workflows that convert unstructured information into structured signals, and factor models that turn those signals into consistent, scalable outputs for individual investors. This role is part of a small and growing, high-caliber team where individuals 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

4+ years of buy-side public markets investing experience, at a hedge fund, long-only fund, family office, or endowment fund that emphasizes long-term investment horizons and independent, fundamental analysis
Experience contributing to a rigorous, process-driven strategy at a successful buy-side firm, including involvement in idea generation, research, and portfolio analysis
Practical LLM workflow experience in equity research workflows (prompt/context engineering; structured extraction; error analysis)
Experience programming, coding or 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 translate fundamental research into a repeatable, systematic strategy, with a strong bias toward building scalable solutions rather than one-off outputs
Multi-sector experience and proven ability to independently perform fundamental research across sectors that has driven long-term investment decisions
Strong forensic accounting knowledge, experience building three-statements and sector-wide models

Responsibilities

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
Develop and evaluate performance of sector-based factor models using a combination of traditional fundamental research, statistical techniques, and quantitative factor design
Oversee stock-picking models alignment to 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 and the ability to influence how the platform evolves
Bonus eligible
Health insurance
Retirement plans
Paid time off