Portfolio Intelligence Analyst

Innovation Endeavors•Palo Alto, CA

10d

About The Position

Innovation Endeavors is a leading early-stage venture capital firm investing in founders who are driving generational change in order to solve problems that matter. We explore how advances in data, computation, and engineering are reshaping industries worldwide. Over 16 years, we have backed breakout companies including Uber, Planet Labs, Viz.ai, AlphaSense, and Kong. We are currently investing out of our fifth fund ($630M), and have total AUM of almost $2B. We invest primarily at Seed and Series A, taking a concentrated, thesis-driven approach, leading nearly every deal and working closely with our portfolio. We are hiring a Portfolio Intelligence Analyst to own and evolve our internal data infrastructure, including the systems, tools, and workflows that power portfolio monitoring, fund management, and investor reporting. You will work directly with our CFO and investment team to turn messy, multi-source data into clean, reliable intelligence that drives better decisions across the firm. This is a high-impact seat at the intersection of data, finance, and technology with visibility intoevery company in our portfolio and direct exposure to how a top-tier VC firm operates. You’ll have the autonomy to build AI-first solutions rather than just maintaining spreadsheets, and you’ll be the firm’s go-to expert on portfolio data. While this role provides visibility and access across the firm, it is not an investing role or a pathway to an investing role.

Requirements

3–5 years of experience in a fast-paced, analytical environment, for example, in a high-growth startup or fund, or data analytics with an investment banking firm.
VC curious with an interest or experience in the innovation economy and venture capital
Data science or analytics training, whether through formal education (degree or coursework in data science, statistics, CS, or a quantitative field) or meaningful professional experience working with data at scale.
Advanced proficiency in Excel/Google Sheets and SQL. Experience with Python, R, or similar tools for data analysis is a strong plus.
Familiarity with AI tools and workflows. You don’t need to be a machine learning engineer, but you should be excited about using AI to solve operational problems and comfortable evaluating new tools.
Working knowledge of finance and accounting fundamentals. Enough to build financial models, understand fund structures, and communicate fluently with the CFO and investment team.
Exceptional communication skills. You can translate complex data into clear narratives for both technical and non-technical audiences.
An ownership mentality. You’re proactive, organized, and comfortable operating with significant autonomy. No task is too small, and no problem is someone else’s.

Nice To Haves

Experience with portfolio monitoring, cap table, or fund admin platforms (e.g.,Standard Metrics, Carta, Investran) is a plus but not required.

Responsibilities

Own the financial data platform. Manage and continuously improve our existing outputs from our accounting system, financing data and cap tables, and our portfolio monitoring platform. Design workflows for data collection, validation, and reporting across our financial reporting and portfolio companies. And more importantly, define and implement future tools for better data management.
Build AI-first tools. Identify opportunities to automate tedious processes—data ingestion, anomaly detection, report generation—using modern AI-first tools. Evaluate and implement new technologies rather than defaulting to manual workflows.
Support fundraising. Assist in drafting the DDQ and other accurate and verified financial fundraising materials for our potential and existing investors. Contribute to fundraising activities by preparing data-backed analysis, and providing transactional and operational support.
Deliver financial analysis. Prepare ad-hoc models and analyses of fund and portfolio performance for quarterly valuations, semi-annual Strategic Reviews, later-stage financing assessments, and LP reporting.
Collect and verify portfolio data. Lead the end-to-end process of gathering financial metrics and KPIs from portfolio companies, foreign company and tax data, while working closely with the CFO and investment team. Ensure data accuracy through systematic verification and reconciliation.
Improve processes relentlessly. Identify bottlenecks and inefficiencies across the firm’s data workflows. Build dashboards, automate reports, and implement best practices for data organization across all firm functions