Research Analyst, Data & Intelligence Products

Research Analyst, Data & Intelligence Products

The Opportunity:

Every day, our reporters and surveys generate intelligence that hedge funds, corp dev teams, consultants, and venture firms would pay real money for. Your job is to work at the intersection of the newsroom and the product team — extracting, structuring, and enriching the proprietary data that powers our intelligence products. Think: company profiles built from exclusive reporting, deal activity timelines, sentiment data from our leadership network, and sector benchmarks drawn from original survey research.

This is a ground-floor role on a small team building something new. You'll have more ownership and visibility than you'd get in three years at a large data or research firm.

What You'll Do:

• Extract and structure intelligence from editorial reporting, surveys, and proprietary datasets into clean, consistent formats (company profiles, deal timelines, executive moves, sector benchmarks).
• Build and maintain taxonomies, tagging systems, and data schemas that make our intelligence searchable and usable at scale.
• Enrich and validate proprietary data — cross-referencing our reporting against public filings, funding databases, and industry sources.
• Help develop new intelligence offerings with survey data from our network of senior tech and finance leaders, identifying trends and signals that feed into intelligence products. By month four you will have launched a new recurring data feed for enterprise clients.
• Work closely with reporters and editors to identify which stories and datasets have the highest commercial value and ensure data quality.
• Support product development by preparing datasets, building prototypes (dashboards, reports, data feeds), and helping define what buyers actually need.

What You Bring:

• 1–3 years of experience in a research, data, or analyst role — at a data/intelligence company, consulting firm, investment firm, media research team, or similar environment. Internships count if the work was substantive.
• Strong data skills. You're comfortable working with messy, semi-structured data and turning it into something clean and usable. Proficiency in Excel is a given; experience with SQL, Python, or similar tools is a plus.
• Fluency with AI and LLM tools. You use ChatGPT, Claude, or similar tools as part of your daily workflow — for research, data extraction, summarization, or prototyping. You have good instincts for where AI accelerates the work and where human judgment is essential.
• Research rigor. You know how to find, verify, and contextualize information. You care about accuracy and can tell when something doesn't add up.
• Familiarity with the tech and business landscape. You follow the industry — you know the difference between a Series B and a growth round, you can name the major players in enterprise AI, and you understand why proprietary intelligence about private companies is valuable.
• Clear communication. You can write a concise summary, explain a dataset to a non-technical stakeholder, and flag issues without being asked.
• Builder mentality. You want to be early at something, not plugged into an existing machine. You're comfortable with ambiguity and motivated by the prospect of shaping a new product from the ground up.

Why This Role

• Unmatched data. You'll work with intelligence that can't be scraped, crowdsourced, or generated by AI — sourced directly from original reporting and a network of over a million senior leaders.
• Outsized ownership. On a small team, your work directly shapes the product. You won't be formatting slides for someone else's presentation.
• Learn the business. You'll get exposure to enterprise product development, go-to-market strategy, and how intelligence companies operate — a career accelerator whether you stay in data, move into product, or go the investor route.

A proven market. AlphaSense, PitchBook, and CB Insights have built multi-billion-dollar businesses selling intelligence to enterprises. You'll help build the version built on truly proprietary, editorially sourced data