Sobre esta vaga de Senior Portfolio Analytics & Investment Associate na Unusual
About the Role
We are seeking an analytically rigorous, commercially sharp Senior Portfolio Analytics & Investment Associate to bridge the gap between structured financial modeling and early-stage startup execution. Positioned within our investment team, this role splits time between delivering strategic insights on portfolio traction, helping with underwriting investments, and serving as a direct fractional financial strategist to our founders.
Unlike traditional back-office data roles, responsibility for institutional fund metrics, DPI/IRR tracking, and Limited Partner (LP) reporting lies entirely with our dedicated Finance team. Instead, you will deliver value by honing internal data infrastructure and advanced analytical modeling to drive proactive investment decision making, assist with pre-investment diligence, and help architect financial strategy alongside our pre-seed and seed-stage portfolio companies from day one.
Core Responsibilities
Portfolio Intelligence & Operational Infrastructure (50%)
Portfolio Modeling: Build and maintain operating models for priority portfolio companies, tracking actuals vs. plan, burn, runway, and progress toward Series A/B milestones and beyond.
Predictive Dashboarding: Engineer internal analytics frameworks and predictive watchlists to monitor portfolio health, alert leadership to real-time runway risks, and evaluate operational velocity. Primary focus is on companies likely to deliver the greatest impact to our funds and put this analysis in front of leadership.
Internal Synergy: Interface directly with the internal Finance team to provide seamless portfolio data information, feeding into valuations for fund accounting and investor reporting.
Investment Evaluation & Due Diligence (25%)
Deep-Dive Due Diligence: Support the commercial evaluation of early-stage investment opportunities, identifying core traction drivers, reviewing financial models and pressure testing assumptions as appropriate.
Investment Committee Memos: Collaborate on drafting high-conviction investment memos and present clear data-driven arguments directly to the Investment Committee.
Market Mapping: Map markets and competitive landscapes across our focus areas (AI infrastructure, developer tools, security, data infrastructure) to support proactive sourcing.
Underwriting & Valuation: Work with other investment team members on complex financial underwriting, cap table dilution analysis, and returns modeling for pipeline opportunities. Support Finance team with valuation modeling as needed.
Founder Advisory & Early-Stage Financial Architecture (25%)
Bespoke Financial Modeling: Embed directly with pre-seed and seed-stage portfolio founders to design, build, and stress-test their initial bottoms-up operational and financial models from scratch.
Strategic Advisory: Translate raw early traction into structured corporate forecasts—optimizing pricing tiers, unit economics, headcount planning, and milestones required to successfully unlock Series A benchmarks.
Capital Raising Support: Partner with portfolio executive teams to build clean, forward-looking runway/burn scenarios ahead of institutional follow-on rounds.
Playbook Development: Institutionalize financial templates across the firm, building robust, repeatable forecasting tooling and playbooks tailored for early-stage B2B SaaS focused in the AI infrastructure segment.
Required Background & Qualifications
Experience: 3–5+ years of experience in either Venture Capital, Private Equity, Growth Equity, or Investment Banking.
Financial Modeling Mastery: Elite-level ability to synthesize complex operational metrics into transparent, flexible three-statement models from a blank sheet of paper.
Early-Stage Intuition: Deep operational empathy for pre-seed and seed founders; a natural ability to educate technical operators on financial literacy and unit economics.
Technical Toolkit: Advanced mastery of Excel/Sheets. Highly value technical familiarity with data management frameworks with MCP integrations (Claude, ChatGPT, Carta), BI visualization software, and standard market information sources (PitchBook, Harmonic, Crunchbase).
Education: Bachelor's degree in Finance, Economics, Computer Science, Engineering, or a highly technical quantitative discipline. MBA/ CFA a plus.