Financial Analyst

About the job

Crossover is a venture capital fund providing diversified access to private technology investing. We invest in pre-seed and seed funds that are often the first call for today’s best founders, as well as select early-stage companies.

Our focus is on backing small funds led by proven founder/operators with established investing track records, where we can draw a direct line between operating experience, network advantage, and access to top technical founders in specific sectors. We also leverage custom-built data systems and close relationships with these managers to identify and directly invest in top-performing companies, alongside leading Series A and B firms.

Crossover operates as a small, tech-forward team led by Silicon Valley veterans with more than 50 years of combined experience building and investing in private technology companies. In addition to delivering top-tier returns, we aim to be the most valuable LP to our fund managers and the most valuable fund manager to our LPs.

Role Overview

We’re hiring a Financial Analyst to own the firm’s portfolio and fund data operations and support core finance workflows. This is a high-trust execution role for someone who is excellent with numbers and data, deeply organized, and comfortable running recurring processes with external partners.

You’ll sit at the intersection of portfolio reporting, data integrity, and fund operations, ensuring that portfolio company and fund reporting flows into our systems cleanly, consistently, and on time. This is not an investing role and does not require financial modeling.

This role is ideal for someone early in their career with strong analytical instincts and high slope—an all-around athlete in a small team, with finance and data as the core.

Location & working style: SF-based hybrid. We expect periodic in-person time for coordination and key cycles; cadence can flex.

Type: Full-time

Benefits: Yes

Compensation: $85,000–$110,000 base (DOE)

Key Responsibilities

1) Portfolio & fund reporting intake (pipeline ownership)

• Manage the ingestion of portfolio company and fund investment reporting (financial statements, schedules of investments, quarterly updates, and related materials).
• Organize and store materials in Google Drive with consistent structure, naming conventions, and version control so information is easy to retrieve and audit-ready.
• Maintain a clear “received vs. missing” view and proactively drive follow-ups when updates are late.

2) Data operations: Airtable as system of record

• Own the quality and completeness of Airtable as the internal system of record for portfolio and fund data.
• Oversee an outsourced team responsible for extracting data and entering it into Airtable, including setting standards, QA checks, and ensuring corrections are made quickly.
• Maintain lightweight data definitions, templates, and validation checks to reduce rework and increase trust in the database over time.

3) Data enrichment & record completeness

• Enrich investment records where possible using web sources, relevant data resources, and internal notes.
• Improve record quality over time by filling gaps, normalizing fields, and keeping key attributes current.
• Coordinate with the team to capture context that matters (e.g., material portfolio updates, financing events, changes in ownership/structure) and ensure it is reflected in Airtable and/or Notion.

4) Valuation policy support (coordination, not analysis)

• Oversee valuation policy support tasks in coordination with the fund administrator.
• Collect, organize, and present relevant portfolio company information needed to support the firm’s valuation policy and quarterly valuation processes.
• Maintain a clean supporting-document trail and trackers so inputs are complete, timely, and easy to review.

5) Small-team projects (as needed)

• As a small firm, we wear multiple hats. You may take on occasional projects that improve operational leverage (process cleanup, vendor coordination, lightweight automation, internal tracking). The core of the role remains finance and data.

What Success Looks Like (first 60-120 days)

• Reporting intake is predictable: materials arrive, are stored correctly in Google Drive, and are easy to retrieve.
• Airtable becomes more trusted: fewer inconsistencies, cleaner records, faster answers to common questions.
• Outsourced data work is high-quality: issues are caught early, resolved quickly, and rework declines over time.
• Valuation policy inputs are organized and complete, with a clear audit trail and on-time delivery.

The Traits We're Looking For

You should strongly identify with the below (and we’ll interview for it):

• High agency: you solve problems without needing step-by-step direction.
• Detail-oriented & organized: you create order and catch what others miss.
• Multi-threaded executor: you can manage several workstreams without dropping accuracy.
• Self-starter: minimal oversight required; strong follow-through.
• Comfort with ambiguity: you can execute even when not all details are finalized.
• Numbers-capable: comfortable in Excel/Google Sheets (basic formulas, reconciliations, simple calculations).
• Clear communicator: crisp written updates, good stakeholder management, strong meeting hygiene.
• No ego / positive: collaborative, calm, low-drama.

Qualifications

• 1–4+ years in a role touching financial operations, fund admin support, portfolio reporting, accounting ops, or data analysis/data operations.
• Strong proficiency with spreadsheets and comfort working with structured data.
• Familiarity with modern tools in a finance/data stack (Google Drive, Airtable, Notion) or the ability to learn quickly.
• High standards for accuracy, documentation, and repeatable processes.
• Comfort handling sensitive financial information and following operational controls and approvals.
• VC/PE/private markets familiarity is a plus, but not required if you learn fast and take ownership.

How to Apply

Send (1) a resume or LinkedIn and (2) a short note answering:

• Describe a process you owned where data accuracy mattered. How did you prevent errors and catch issues?
• What’s an example of improving a recurring workflow (tracker, template, QA checks, automation)?
• What tools have you used to manage reporting intake, data ingestion, or structured datasets?