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.Our Corporate Finance team, part of Finance Data Science and Engineering (DSE), brings this same innovative approach to our financial operations. As trusted partners to our finance stakeholders, we analyze key metrics, surface actionable insights, and drive value for the business. As Netflix continues to grow, the need for advanced analytics in Finance is greater than ever – leveraging cutting-edge techniques to uncover deeper insights and identify new opportunities for impact.You’ll play a key role in shaping the future of advanced analytics within Corporate Finance at Netflix, helping to unlock new value and drive strategic decision-making through data. Learn more from our blog on how Finance AEs are driving the business forward through data. In this role, you will:Partner with Analytics Engineering, Data Science, Data Engineering, and cross-functional Finance teams to uncover data opportunities where advanced analytics (think: forecasting, classification) can provide actionable insights.Lead advanced analytics projects in key Corporate Finance areas (e.g., spend classification modeling, forecasting general ledger categories, and other greenfield opportunities in procurement, operations, and strategy).Create and curate robust datasets and data pipelines from structured finance data sources (revenue, expenses, accounting journal entries, vendor invoices) to unlock insights and identify patterns.Productionize analytics models in partnership with Data Science and Data Engineering teams, focusing on practical, scalable solutions.Help upskill the team on when and how to use classical machine learning and modeling techniques, and when simpler analytics approaches are more appropriate.Technical Skills:Demonstrated ability to write clean, readable, and impactful SQL code.Strong proficiency in Python (including notebooks and modeling skills).Advanced SQL skills for analytics data processing (e.g., splitting data into train/eval/test sets).Experience with AI tools for automation (e.g., Cursor, Claude, Commands, Rules) is a plus.Familiarity with DBT or other semantic data modeling tools for strong data foundationsWhat Sets You Apart:3+ years of experience in analytics engineering, data science, or a similar data-focused role, ideally with a strong focus or interest in finance.Solid statistical foundation, or a strong interest in upskilling in statistics and classical machine learning.Examples of applying classical ML techniques (such as classification or forecasting) to real-world problems, especially in the finance domain, are a strong plus.Excellent communication skills, with the ability to translate complex data insights into clear, actionable recommendations for both technical and non-technical stakeholders.Collaborative approach and a passion for continuous learning and innovation.Our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $170,000 - $720,000.Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more detail about our Benefits here.Netflix has a unique culture and environment. Learn more here.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.
Locations
Los Gatos, California, United States of America
Salary
170,000 - 720,000 USD / yearly
Estimated Salary Rangemedium confidence
180,000 - 250,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
write clean, readable, and impactful SQL codeintermediate
proficiency in Python (including notebooks and modeling skills)intermediate
Advanced SQL skills for analytics data processingintermediate
Experience with AI tools for automationintermediate
Familiarity with DBT or other semantic data modeling toolsintermediate
Required Qualifications
3+ years of experience in analytics engineering, data science, or a similar data-focused role, ideally with a strong focus or interest in finance. (experience, 3 years)
Solid statistical foundation, or a strong interest in upskilling in statistics and classical machine learning. (experience)
Examples of applying classical ML techniques (such as classification or forecasting) to real-world problems, especially in the finance domain, are a strong plus. (experience)
Excellent communication skills, with the ability to translate complex data insights into clear, actionable recommendations for both technical and non-technical stakeholders. (experience)
Collaborative approach and a passion for continuous learning and innovation. (experience)
Preferred Qualifications
Experience with AI tools for automation (e.g., Cursor, Claude, Commands, Rules) is a plus. (experience)
Examples of applying classical ML techniques (such as classification or forecasting) to real-world problems, especially in the finance domain, are a strong plus. (experience)
Responsibilities
Partner with Analytics Engineering, Data Science, Data Engineering, and cross-functional Finance teams to uncover data opportunities where advanced analytics (think: forecasting, classification) can provide actionable insights.
Lead advanced analytics projects in key Corporate Finance areas (e.g., spend classification modeling, forecasting general ledger categories, and other greenfield opportunities in procurement, operations, and strategy).
Create and curate robust datasets and data pipelines from structured finance data sources (revenue, expenses, accounting journal entries, vendor invoices) to unlock insights and identify patterns.
Productionize analytics models in partnership with Data Science and Data Engineering teams, focusing on practical, scalable solutions.
Help upskill the team on when and how to use classical machine learning and modeling techniques, and when simpler analytics approaches are more appropriate.
Benefits
general: Health Plans
general: Mental Health support
general: a 401(k) Retirement Plan with employer match
general: Stock Option Program
general: Disability Programs
general: Health Savings and Flexible Spending Accounts
general: Family-forming benefits
general: Life and Serious Injury Benefits
general: paid leave of absence programs
general: Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off.
general: Full-time salaried employees are immediately entitled to flexible time off.
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