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Analytics Engineer (L4) - Corporate Finance

Netflix LogoNetflix
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Salary

$170,000 - $720,000

Location

Los Gatos, CA

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 foundations

What 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.

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