Decile Group

Decile Group

Start Fund Investment Lead

Palo Alto

Sponsorship not specifiedDetected 345 days ago

About the role

  • Are you a driven professional with a vision for the future of venture capital?
  • Scam Warning VC Lab and Decile Group never conduct screening interviews via chat, and we will never ask candidates to send money, purchase equipment, or share financial information.
  • Scammers may impersonate real employee names.

Responsibilities

  • By applying, you are expressing interest in becoming an Investment Lead on the Start Fund platform to launch and manage your own venture capital fund.
  • Your reward is the opportunity to build, own, and grow your own fund with comprehensive support and industry-leading infrastructure from Decile Group.
  • Do you want to launch your own VC fund quickly and efficiently, with comprehensive support and minimal barriers?
  • Start Fund is an innovative, institutional-grade VC fund structure that enables Investment Leads to launch a fully operational fund in less than one business day, with no upfront expenses.
  • Optimized for flexibility and speed, Start Fund supports fund sizes as small as $150K and LP investments starting at $10K.
  • Decile Group manages all compliance, legal, and administrative matters, allowing you to focus on building your portfolio and network.

Compensation

  • Important Note This is not a paid employment opportunity.
  • By applying, you are expressing interest in becoming an Investment Lead on the Start Fund platform to launch and manage your own venture capital fund.
  • There is no salary or compensation.
  • Your reward is the opportunity to build, own, and grow your own fund with comprehensive support and industry-leading infrastructure from Decile Group.

Benefits

  • Decile Group invites you to become an Investment Lead on Start Fund, a flexible platform designed to simplify fund formation and support emerging managers.
  • Benefits of Start Fund

This listing is sourced directly from Decile Group's careers page and normalized into a canonical job model.