Janestreet

Janestreet

Compensation Specialist

New York, New York, United States

Sponsorship not specifiedDetected 71 days ago
ExcelCompensationAdaptability

About the role

  • We are looking for a detail-oriented Compensation Specialist to help our growing Compensation team with a wide range of operations and analytical work, while partnering closely with many teams, managers, and employees across the firm.
  • Day to day, you will support high-volume compensation operations, including offer modeling and production, as well as year-end processes and a variety of other operational workflows. You will also take on some analytical and project-based work, such as participating in broad market data surveys, conducting compensation deep dives on specific job families,

Nice to have

  • Have 2-5 years of compensation-specific experience, or a mix of compensation and related HR roles (e.g., operations, analytics, HRBP)
  • Compensation consulting experience is a plus, but not required
  • any industry background is welcome
  • Comfortable with technology and willing to learn our internal tools
  • having an interest in picking up light coding is a plus
  • Detail-oriented with a high accuracy bar
  • discreet and trustworthy with sensitive compensation data
  • A strong written and verbal communicator

Skills

  • Analyzing candidate long-term incentive structures, such as RSU vesting schedules and buyout valuations
  • Speaking directly with candidates to explain our compensation philosophy and walk through offers
  • Supporting our annual compensation planning cycles and related operational processes
  • Getting comfortable with our internal tools, with the potential to eventually learn some light coding

Compensation

  • We are looking for a detail-oriented Compensation Specialist to help our growing Compensation team with a wide range of operations and analytical work, while partnering closely with many teams, managers, and employees across the firm.

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