Arcanaanalytics

Arcanaanalytics

Sales Development Representative

New York, United States

Sponsorship not specifiedDetected 1 day ago
HubSpotSalesforceCRMSalesResearchCommunicationCFA

About the role

  • You'll identify, research, and engage prospective clients across the hedge fund and asset management ecosystem-partnering closely with sales, marketing, and product to open high-value opportunities and define how we reach new clients.
  • If you're looking to rocket-ship your career and work alongside a top-performing sales team (ex-AlphaSense, Visible Alpha, MSCI), we'd love to talk.

Responsibilities

  • Identify and research target hedge funds, asset managers, and allocators to build high-quality prospect lists
  • Collaborate closely with Sales Directors to develop account strategies and book qualified discovery meetings

Requirements

  • 2+ years of experience in a client-facing role within financial services or enterprise SaaS, with direct exposure to institutional clients (hedge funds, asset managers, allocators, etc.)
  • Familiarity with portfolio analytics, investment concepts, and institutional workflows (e.g. attribution, alpha/beta, drawdowns, correlation, etc.)
  • Bachelor's or Master's degree in Finance, Economics, Business, or a related field
  • Experience with Bloomberg, FactSet, or portfolio analytics platforms is helpful
  • Familiarity with equity risk models and factor-based investment frameworks is helpful

Nice to have

  • Experience with CRM tools (Salesforce, HubSpot, or similar) preferred
  • Prior exposure to hedge funds, asset managers, or investment technology is a plus
  • CFA, FRM, or MBA is a strong plus

Skills

  • Arcana is a portfolio intelligence platform used by hedge funds and asset managers to analyze performance and risk.

Compensation

  • Competitive base salary

Benefits

  • Performance-based bonus tied to key sales metrics, including number of qualified meetings booked, and pipeline created.

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