Equity Research Analyst

Fiscal.ai

1d•Remote

About The Position

Fiscal.ai is a leading research and data platform built for capital markets professionals. Combining a high-performance research Terminal with a modern, near-real-time fundamentals API and MCP server, Fiscal.ai is redefining financial data infrastructure for the AI era. The company serves thousands of institutional and professional Clients while reaching millions of end-users through API Clients. If you have strong financial and investing acumen and want to build a best-in-class fundamental data product, this is the role for you. This is not a traditional finance role. You might come from equity research, investment banking, asset management, or an accounting background. What matters is that you understand how investors actually use fundamental data and you're excited to build the systems that deliver it. You'll own the logic that transforms raw public disclosures into structured, API-ready datasets powering institutional finance and investing workflows. That means designing data structures, building transformation rules, expanding coverage across markets, and owning the integrity of everything we deliver. You'll work directly with our COO, taking full ownership of our data capture and processing systems while maintaining the rigor our clients expect.

Requirements

Deep understanding of finance and investing, and genuine excitement to build a data product for investors
2-5 years across accounting, finance, investing, and/or data roles
Strong data and analysis skills with awareness of multiple accounting standards and jurisdictions
Naturally curious systems thinker with strong pattern recognition, ability to connect the dots, and comfort with ambiguity
Self-directed, resourceful, and a clear communicator
Excited to work at a fast-growing startup

Nice To Haves

CPA or CFA is an asset

Responsibilities

Design and maintain classification systems for public financial disclosures across jurisdictions
Build rules that transform unstructured data into normalized, queryable datasets
Research disclosure requirements in new markets and map jurisdiction-specific nuances into our data model
Work with LLMs to write and refine prompts, build and test logic, and iterate based on outputs
Partner with QA and engineering to identify edge cases and validate data accuracy
Identify coverage opportunities and prioritize based on commercial signal
Translate internal and external feedback into strong systems
Support leading R&D on new data capabilities and product development