Netflix

Netflix

Manager, Sales Incentive Compensation

New York,New York,United States of America · Senior · Contract

Sponsorship not specified$225k-$370kDetected 19 days ago
Project ManagementSalesforceCRMSalesFinancial ModelingExcelFP&ACommunicationCollaborationProblem Solving

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odds of building a lasting career here

64Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role100
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

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Employer immigration record

from this employer's Department of Labor filings

Green-card follow-through: 85%

Of 40 labor certifications old enough to have been used, 6 expired without the employer filing the next step. Median time from filing to decision: 496 days.100% of their filings were for a worker who already held the job.Only certifications past the 180-day window are counted — recent ones cannot have expired yet.

Files H-1B transfers

160 transfer filings in the last year, covering 388 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

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About the role

  • They've shown real AI capability, having implemented practical AI solutions within an SIC program.
  • This includes plan change impact modeling, financial modeling, and feasibility assessments.
  • This role is accountable for delivering SIC plans through operational processes and tools, ensuring payment accuracy.

Responsibilities

  • Build a mechanism for Incentive Plan Design proposal intake and assessment.
  • Operate as a critical input/voice in the Incentive Plan Design proposal development and approval process.
  • Develop operational plans to support Incentive Plan Design implementation.
  • Partner with SalesOps, FP&A, Central Revenue Ops, Ads Product Tech, Sales, and HRBP to negotiate alignment on operational plans and SLAs for Incentive Plans.
  • Perform feasibility assessments for Incentive Plan proposals, including operational cost modeling and projecting outcomes.
  • Create efficient and simple workflows and solutions to support approved Incentive Plans. This may include project management of temporary manual workflows, automation, tool builds, policy creation, and other solutions as needed.
  • Develop Sales Readiness plans for rollout of Incentive Plan Design changes and updates. Will also deliver sales training, at times.
  • Drive simplicity and efficiency through Sales Incentive Compensation operations through a continuous improvement approach. Accountable for full Incentive Plan lifecycle design.

Requirements

  • Bachelor's degree in related field
  • 7+ years of sales incentive compensation, FP&A, or sales operations experience
  • Experience working with Sales CRM and SIC tools (such as Salesforce and CaptivateIQ/Xactly/SPIFF)
  • Experience implementing variable sales compensation plans
  • Demonstrated experience delivering SIC solutions with AI tools (Cowork, Gemini, etc.)
  • Ability to define, aggregate, and analyze metrics to assess performance drivers
  • Experience setting, interpreting and governing policies for a global program
  • Experience with sales incentive compensation models for advertising/media

Compensation

  • $225k-$370k

Company info

  • At Netflix, our mission is to entertain the world.
  • Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality.
  • We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology.

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