hero

Compa Community Jobs

Discover open compensation roles across our Compa Index community network
Hero Box Icon

VP and Above

View Roles
Hero Box Icon

Senior and Director roles

View Roles
Hero Box Icon

Entry Level

View Roles
companies
Jobs

Compensation Analytics Partner - APAC

Netflix

Netflix

Singapore
Posted on Mar 13, 2026

Netflix is one of the world's leading entertainment services, with over 300 million paid memberships in over 190 countries enjoying TV series, films and games across a wide variety of genres and languages. Members can play, pause and resume watching as much as they want, anytime, anywhere, and can change their plans at any time.

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. Come be a part of what’s next.

To deliver on this vision, we need strong candidates who can operate beyond conventional structures. To that end, we’re seeking a Compensation Analytics Partner to support our growing business in APAC.

This role will be responsible for building and establishing the analytical and structural foundation of compensation programs, with a strong mandate to design scalable data models and enable data- and evidence-informed decisions that align with long-term business needs.

Key Responsibilities

  • Leads the annual Market Compensation Review cycle in APAC.

  • Work closely with the Compensation Team to develop market review principles and approaches for their respective functional areas.

  • Collaborate with the Job Architecture team to assess and validate roles across APAC, ensuring the structure appropriately reflects role scope, complexity, and alignment with the global framework.

  • Lead and manage job profiles audit.

  • Partner with Talent Acquisition to explore opportunities to further enhance the job offers process, including the selection of job profiles and analysis of offers.

  • Lead the analysis of complex compensation data, including cost modeling, employee impact analysis, and market intelligence, to inform decision-making and support strategic recommendations.

  • Provide forward-looking insights to enable compensation business partners to focus on strategic advisory

  • Communicate complex compensation topics with clarity and confidence to leaders and cross-functional partners.

What we are looking for

  • Strong technical skills in data analysis (SQL, Python/R, or equivalent), and visualization tools (e.g., Tableau, Power BI).

  • Proven ability to manage large datasets from multiple sources and translate them into meaningful recommendations.

  • Experience with compensation survey vendors (e.g., Mercer, Radford, Willis Towers Watson) and recruiting data sources.

  • Strong business acumen and ability to collaborate with HR, recruiting, and finance teams.

  • Strong analytical skills with the ability to tell stories with data.

  • Strong communication skills, with the ability to convey complex information clearly and concisely.

  • Strong understanding of compensation data and systems, with experience in auditing and maintaining data integrity.

  • A proactive and solution-oriented approach, with the ability to navigate ambiguity and drive process improvements.

  • Workday compensation module and benchmarking tool experience (e.g., BetterComp, MarketPay, CompAnalyst) preferred

Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.

We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.