Associate, Payments Strategy & Analytics (Technical) - APAC

Netflix is one of the world's leading entertainment services, with 283 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.

The APAC Finance & Strategy (F&S) Commerce Payments team is looking for high-caliber talent to focus on payment analytics. You play an essential role in leading day-to-day efforts to monitor payment performance and drive analyses that increase subscriber acquisition, improve retention, and maximize revenues. You will be part of the team responsible for turning payments data into business and product insights that inform and develop our payments strategy.

RESPONSIBILITIES:

• Monitor the performance of payments processing (e.g., payments page conversion and customer retention performance driven by payments) across a number of markets and payment methods: cards, wallets, direct carrier billing, and bank-based payments.

• Lead strategic analyses and partner with Payments Managers and Product Managers to help identify, prioritize, and assess the impact of new initiatives. This includes working cross-functionally throughout the organization with a large number of potential stakeholders (e.g. payments, finance, data science and analytics, consumer insights, engineering, etc.)

• Support payment partner engagement with digital wallets, banking institutions, gift card service providers, and card networks (e.g. Visa/Mastercard) with a focus on improving performance

• Proactively identify the opportunities most important for growth (acquisition, retention, and revenue) and create insightful presentations that facilitate decision-making for internal stakeholders and our external partners.

• Collaborate with your peers in other F&S functions (content, marketing, partnerships, etc.) to develop a holistic view of the business on a market level.

• Optimizing our analytical models and working with data engineering to maintain data quality will improve our analytical tooling and efficiency.

QUALIFICATIONS:

Netflix is growing fast with a flat organizational structure, which means that employees are often asked to perform tasks with a range of difficulties. The ideal candidate will be prepared to regularly “roll up their sleeves” to perform more mundane tasks on the same day that they present to the executives of the company. Candidates must be curious, motivated, disciplined, and able to work autonomously.

• Minimum 7 years of experience in an analytical role. Excellent analytical skills including the ability to use business intelligence tools (SQL and Tableau), build spreadsheet models, sort through complex data to crystallize business implications, and craft a data-driven story.

• Excellent at turning business questions into analytical plans and connecting insights to product-oriented actions.

• Strong payments experience focused on how to improve payment processes, at a leading or startup tech company preferred.

• Ability to engage, listen, and collaborate with internal teams to align from ideation through execution to launch.

• Self-driven, comfortable with a fast-paced, always-on, highly ambiguous environment.

• Capable of remaining highly organized and aligned in a loosely structured organization.

• Excellent verbal and written communication skills.

• Bachelor’s degree in finance, economics, mathematics, statistics or other relevant field preferred

• Additional language skills are a plus.

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.