Sr. Equity Research Analyst, AI Platform at Versant

Englewood Cliffs, New Jersey, United States -

Full Time

Start Date

Immediate

Expiry Date

28 Jul, 26

Salary

235000.0

Posted On

29 Apr, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Equity research, Public markets investing, LLM workflows, Prompt engineering, Structured extraction, Factor models, Quantitative analysis, Forensic accounting, Three-statement modeling, Data analysis, Programming, Python, API development, Backtesting, Financial modeling, Investment strategy

Industry

Marketing Services

Description

Company Description About Versant 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. We continue operating like a startup: small team, high ownership, fast decisions, direct access to leadership, and a culture focused on building rather than managing. At the same time, we have 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 our team. That means the upside of a fast-paced builder environment without the fragility and resource constraints of a typical early-stage startup. Our mission is to help millions of investors achieve better results in the markets. This is your chance to work at the intersection of investing, AI, and product, alongside other exceptional engineers and investors, and help define what modern equity research looks like. Job Description We're looking for a highly driven and intellectually curious equity analyst to join our team to build a new generation of AI-powered equity research. 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 build and operate 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. This role sits within a small and growing, high-caliber team where individuals 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. Qualifications What We're Looking For: · 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 What You'll Do: · 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 Location & Perks: At CNBC Headquarters in Englewood Cliffs, NJ, you’ll have access to great perks and amenities: • Sweat it out -- Free onsite fitness center with state-of-the-art equipment, plus daily group classes • Eat up -- Gourmet cafeteria with daily specials plus soup and salad bars • Extras -- Dry cleaning, shoe shining and sneak peeks • Don’t have a car? No problem! We offer free shuttle transportation to and from multiple locations in Manhattan, Brooklyn, Hoboken and Jersey City In addition to these benefits, employees in this group will be joining at a time of meaningful and continued investment in data, technology, and product development, with the opportunity to contribute to a growing team within CNBC that is expected to scale significantly over time, offering meaningful exposure to senior leadership and the ability to influence how the platform evolves. Salary Range: $200,000-$235,000, bonus eligible. Additional Information As part of our selection process, external candidates may be required to attend an in-person interview with a VERSANT Media employee at one of our locations prior to a hiring decision. VERSANT Media's policy is to provide equal employment opportunities to all applicants and employees without regard to race, color, religion, creed, gender, gender identity or expression, age, national origin or ancestry, citizenship, disability, sexual orientation, marital status, pregnancy, veteran status, membership in the uniformed services, genetic information, or any other basis protected by applicable law. If you are a qualified individual with a disability or a disabled veteran and require support throughout the application and/or recruitment process as a result of your disability, you have the right to request a reasonable accommodation. You can submit your request to [email protected]. VERSANT Media is committed to fair and equitable compensation practices. We include a good faith pay range for each position to comply with applicable state and local pay transparency laws and to promote equity across our organization. Actual compensation will be based on factors such as the candidate's skills, qualifications, experience, and location and may include additional forms of compensation and benefits such as health insurance, retirement plans, paid time off, etc. VERSANT Media is not accepting unsolicited assistance from search firms for this employment opportunity. All resumes submitted by search firms to any employee at VERSANT via-email, the Internet, or in any form and/or method without a valid written Statement of Work in place for this position from VERSANT's Talent Acquisition team will be deemed the sole property of VERSANT. No fee will be paid in the event the candidate is hired by VERSANT as a result of the referral or through other means. Business Segment: CNBC Compensation: USD 200000 - USD 235000 - yearly

Responsibilities

You will build and operate AI-powered equity research workflows, including LLM-based signal extraction and sector-based factor models. You will also partner with engineering to implement scalable pipelines and deliver actionable stock insights to retail investors.