Penn National Gaming Referral Bonus Overview

Penn National Gaming offers a referral bonus program designed to incentivize current employees to refer qualified candidates for open positions within the company. This program is particularly appealing for those looking to join the tech and product teams, although it is also applicable to other roles within the organization.

Referral Bonus Structure

• Tech/Product Roles:

  • Bonus Amount: The referral bonus for tech and product roles ranges from $2,000 to $5,000, depending on the position's level and criticality.
  • Payment Structure: The bonus is typically paid out in two installments. The first half is paid when the referred candidate completes 90 days of employment, and the second half is paid after the candidate reaches their one-year anniversary.

• Other Roles:

  • Bonus Amount: For non-tech roles, bonuses generally range from $500 to $2,000.
  • Payment Structure: Similar to tech roles, these bonuses are also paid in two installments, with conditions based on the candidate's tenure.

Eligibility Criteria

• Referrer Eligibility: Only current employees of Penn National Gaming are eligible to receive referral bonuses.
• Candidate Criteria: The referred candidate must be a new applicant who has not applied for any position at Penn National Gaming in the past 12 months.
• Successful Hire: The referred candidate must be successfully hired and meet the employment duration requirements as outlined above.

Additional Details

• Multiple Referrals: If multiple employees refer the same candidate, the referral bonus is typically awarded to the employee whose submission was received first.
• Exclusions: The program may exclude certain positions or levels, such as executive roles, from eligibility for referral bonuses.
• Program Updates: The referral bonus program is subject to change, and employees are encouraged to check the internal HR portal for the most current details.

This referral bonus program underscores Penn National Gaming's commitment to attracting top talent by leveraging the networks of its current