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Netflix

Analytics Engineer 5 - Business Forecasting

Posted Yesterday
Remote
Hiring Remotely in USA
330K-566K Annually
Senior level
Remote
Hiring Remotely in USA
330K-566K Annually
Senior level
Collaborate with stakeholders to analyze data and metrics, implement analytical models, and enhance data quality for business forecasting.
The summary above was generated by AI

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.

We have more than 300 million members in 190 countries, reflecting that great stories can come from anywhere and be loved everywhere. We now have a portfolio that includes subscriptions, advertising, and gaming, and we're redefining what it means to build products at a global scale. The commerce team strives to build lasting relationships with our future and existing members by providing opportunities to engage with our various offerings, providing a variety of ways to access, experience, and pay for Netflix.

Data is at the heart of our commerce strategy. Our Commerce Data Science and Engineering team works with a broad range of collaborators and stakeholders, including Product, Engineering, and Finance, to inform commerce strategy and data-informed decision-making through analysis, metrics research, experimentation, causal inference, and modeling, as well as through exceptional judgment, partnership, and business acumen. 

Sitting within Commerce DSE, the Subscription Revenue Data Science team is responsible for building a scientific backend for many of our most important business forecasts- consumer acquisition, churn, and total revenue. We are maturing our forecasts into a data product that is useful across a broad set of use cases and stakeholders. Our mission is to deliver accurate, consistent, and scaled forecasts to drive a range of business planning use-cases like pricing and content investment

We are hiring a founding Analytics Engineer to help scale this space. As an Analytics Engineer, you will join a team of other stunning Analytics Engineers, Data Scientists, and Machine Learning Scientists. You will help stakeholders understand what our forecasts say, and why. You will collaborate with the commerce team, data engineers, and analysts to provide insights and tooling to scale data-driven decision-making for Netflix.

In this role, you will:

  • Partner directly with our cross-functional stakeholders on data, metrics & analytics initiatives

  • Proactively identify and perform data exploration and deep dives to influence future product directions 

  • Develop and validate the appropriate metrics to measure success in the identity space

  • Improve foundational data models while designing, owning, and implementing analytical layers and visualizations for scalable analytics

  • Collaborate with the data engineering and data science teams to ensure data quality, integrity, and availability for analysis

  • Contribute to the excellence of the Netflix analytics engineering community 

  • Live Netflix values while bringing a new perspective to continue improving our culture

To be successful in this role, you have:

  • 5+ years of industry experience in a data analytics or data science function 

  • Expertise in SQL, programming skills (e.g., Python or R, Scala), and some exposure to ETL and data warehousing concepts

  • A proven track record of data analysis, maintaining analytical layers, reporting, and visualization (e.g., Plotly Dash, Streamlit, Tableau)

  • Exceptional communication, storytelling, and collaboration skills coupled with strong business curiosity and acumen

  • Comfort with ambiguity; able to take ownership, and thrive with minimal oversight and process

  • Experience managing expectations and relationships across a variety of stakeholders

  • An interest in Netflix culture

  • Familiarity with applied A/B testing experimentation fundamentals is a plus


Generally, 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 $330,000.00 - $566,000.00. This compensation range will vary based on location.

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 details about our Benefits here.

Netflix is 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.

Job is open for no less than 7 days and will be removed when the position is filled.

Top Skills

Data Warehousing
ETL
Plotly Dash
Python
R
Scala
SQL
Streamlit
Tableau

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