VC Analyst @ Crossover VC in San Francisco, CA

About Crossover VC

Crossover is an early-stage venture capital fund that combines diversified exposure to small, high-access pre-seed and seed funds with concentrated direct investments in the breakout companies they surface.

We back founder- and operator-led funds with privileged access to the talent-dense ecosystems where the next generation of category-defining companies is being formed. We then use proprietary portfolio data and our relationships with those managers to identify the highest-potential companies early and invest directly 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 Description

We’re hiring an Investment Analyst to help build and continuously improve the data, analytical tools, and systems that support Crossover’s investment and operations activities.

This is a high-trust, high-agency role at the intersection of investing, data, AI, and operations. You will work closely with the Managing Partner and operations teams across our fund portfolio, more than a thousand underlying companies, and Crossover’s direct investments.

A core part of Crossover’s strategy is using proprietary information from our fund portfolio to make better investment decisions. We want someone who can structure that information, combine it with external data, and use analysis and modern AI tools to surface insights. The role is well suited to someone who is analytically curious, familiar with modern AI tools, and interested in venture investing.

What You’ll Own

Investment Data & Internal Systems

• Manage the collection, ingestion, and quality of data from underlying funds, portfolio companies, financing announcements, and other relevant sources.
• Own and improve Crossover’s proprietary datasets and internal systems, including Airtable and custom-built AI workflows.
• Analyze fund and company data to identify trends, portfolio developments, and potential investment opportunities, and combine proprietary information with external data to answer investment questions.
• Develop processes, taxonomies, QA checks, and automation that improve data quality, reduce manual work, and make information easier for the investment team to use.
• Help build and improve AI-enabled tools for investment research, portfolio monitoring, sourcing, and analysis.

Investment & Portfolio Operations

• Support fund and company diligence through research, data collection, and analysis.
• Maintain accurate investment records, ownership information, portfolio data, and supporting materials.
• Monitor underlying funds and portfolio companies for financings, material developments, and other relevant activity, and ensure important information is captured in our systems.
• Support special projects related to fund evaluation, direct investments, portfolio construction, market mapping, and investment strategy.

As part of a small team, you will also be expected to take on projects and responsibilities outside these core areas when needed.

What Success Looks Like

Over time, success in this role means:

• Our proprietary fund and company data becomes increasingly accurate, complete, and useful to the investment team.
• Data and analysis increasingly help answer investment questions and surface interesting companies, opportunities, and portfolio trends.
• Recurring research and data processes become simpler and more automated, with AI-enabled workflows becoming a practical part of how Crossover conducts research and monitors investments.

The ultimate goal is to make Crossover’s data increasingly useful to how we invest.

Who We’re Looking For

We care more about slope, judgment, and ownership than checking every box. The strongest candidates will likely have 2–5+ years of professional experience in an analytically rigorous environment.

• High agency. You solve problems without needing step-by-step instructions.
• Analytically curious. You enjoy digging into data, identifying patterns, and understanding what the information actually means.
• Exceptional attention to detail. You care about the quality of the underlying data and naturally catch inconsistencies others miss.
• Systems thinker. When you encounter a recurring process, you think about how it can be improved, standardized, or automated.
• Technically curious. You actively use modern software and AI tools and are interested in how they can improve investment research and decision-making. You do not need to know how to code or have a software engineering background.
• Investment-oriented. You are genuinely interested in venture capital, technology companies, markets, and what makes funds and companies successful.
• Low ego. You are equally willing to clean a dataset, improve a workflow, or dig into an investment question.

Experience That Could Be a Fit

There isn’t one required background. Strong candidates could include:

• A financial or investment analyst from investment banking, private equity, venture capital, or another rigorous financial environment.
• A data, operations, strategy, or business operations professional from a startup or technology company who wants to move closer to investing.
• Someone with a few years of operating or analytical experience followed by a top business school who is looking to build a career in the venture ecosystem.
• A professional from consulting, private-markets software, data, research, or another analytically rigorous environment.

Direct venture capital experience is helpful but not required. We would rather hire an exceptional generalist who is curious, learns quickly, and takes ownership than someone with the perfect resume who waits to be told what to do.

Tools and Capabilities

You should be highly proficient with spreadsheets and structured data and comfortable learning new software quickly. Experience with Airtable, SQL, Python, data visualization, APIs, or AI-enabled workflow tools is helpful but not required.

Location and Working Style

This is a San Francisco Bay Area-based hybrid role. We believe there is meaningful value in working together in person, particularly for investment discussions, collaborative analysis, and building new systems, with flexibility to work remotely.

Compensation

The expected base salary range is $125,000–$160,000, depending on experience and fit, plus an annual performance bonus and benefits. For exceptional candidates who can grow with Crossover over the long term, the package may also include participation in the economics of the firm.

Why Crossover

• You will work with a differentiated dataset generated through Crossover’s investments in early-stage venture funds led by founders and operators from companies including Mercury, Instacart, Databricks, OpenAI, and others, as well as the hundreds of underlying portfolio companies those funds back.
• You will have meaningful exposure to fund and direct investing, while having significant latitude to improve how we collect, analyze, and use investment data.

We believe software, data, and AI will change how investment firms operate. We want someone excited to help us turn access to information into an investment advantage and grow with Crossover over time.

How to Apply

Please apply here or email hello@crossovervc.com with “Investment Analyst” in the subject line. Include your resume and a short note explaining why you’re interested in the role and why you believe you’d be a strong fit.