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. The team you will join: Our team uses data for the consumer product security in two ways: 1) provide insights into effectiveness of security measures across products, and 2) build intelligence to address fraud in scale. Examples of fraud we deal with include account compromise, piracy, and DDoS. We achieve our goals through both technical work on the team and cross-functional partnerships. We are looking for an analytics engineer to join our team to drive security metrics as well as data solutions for detection and prevention across the fraud landscape. If you've used Netflix, you've been protected by systems that our team built. We collaborate closely with Product, engineering, Data teams, as we believe security is a team sport. This blog post is a great way to learn about our work. What you will work on: As a Security Analytics Engineer, you will drive insights and discovery of fraud in our ecosystem by understanding our infrastructure, and product, identifying high risk areas, and driving changes to our anomaly detection and product experiences. You will leverage your security and fraud prevention expertise to analyze patterns, identify new signals, and recommend adjustments based on impact to our customers and Netflix. - Develop data-driven insights to influence our device & product security strategy, including identifying new signals for anomaly detection - Compile and track anomalous request patterns and identify potential mitigations - Design and champion data‑driven security enhancements that strengthen our devices and safeguard our rich content catalog. - Analyze error logs to quantify potential device-level vulnerabilities - Develop characterizations of request attributes across a diverse device and client ecosystem to quantify potential automation - Build insights into security and identity of the Netflix diverse and large-scale device ecosystem and develop dashboards to cascade the insights to a wide range of stakeholders Desired skills and background: - Passionate about protecting our customers & products. - Expert with analytics (SQL, Presto, sparkSql, python) and critical thinking. - Experience in signal development for classification and anomaly detection - Experience in metrics development and storytelling that drive business decisions. - Familiarity with various aspects of fraud and abuse types, including account compromise, piracy, or DDoS. - A strong communicator & collaborator in varying contexts & environments. 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 $250,000.00 - $421,000.00. 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.

Role Description FlowMo builds AI systems that turn business data into real work. This role is for someone who can take messy data and produce answers quickly using data modeling best practices. - Build data models using SQL and DBT/LookML-style logic - Answer core business questions such as CAC, LTV, attribution, and revenue drivers - Debug and fix broken or incomplete datasets - Translate business questions into structured data models - Iterate quickly and improve outputs over time - Ship usable results fast, not perfect results slowly Qualifications - 2–5+ years working in data modelling in a business context - Experience with data modeling tools (DBT, LookML, or similar) - Comfortable working with messy or incomplete data - Strong written and spoken English - Ability to work overlapping U.S. hours (EST) - Ability to operate independently with minimal structure Requirements - Fast-paced environment with minimal process and bureaucracy - Opportunity to grow into a customer-facing analytics or solutions role - Work directly with founders and core product team - Flexible, remote-first work environment Benefits - This is a remote role within a small, fast-moving team. Independence, speed, and ownership are essential. - Work with real customer data from day one - Operate with minimal structure and high accountability - Iterate quickly and learn by doing - We value people who can figure things out and ship results. Application Process - Apply with your responses to the required questions - Short (30-minute) interview - Fast decision Company Description FlowMo connects a DTC brand's stack (Shopify, GA4, Meta, Google Ads, Klaviyo, and more) once, then runs deterministic AI on top of a semantic data model to go from data → insight → recommendation → action. Operators and agencies see value by day 2 (with your help). No new stack, no data team, no dashboard fatigue. Every competitor (Triple Whale, Northbeam) stops at insight. We do the work.

• Build data models using SQL and DBT/LookML-style logic • Answer core business questions such as CAC, LTV, attribution, and revenue drivers • Debug and fix broken or incomplete datasets • Translate business questions into structured data models • Iterate quickly and improve outputs over time • Ship usable results fast, not perfect results slowly

• Build data models using SQL and DBT/LookML-style logic • Answer core business questions such as CAC, LTV, attribution, and revenue drivers • Debug and fix broken or incomplete datasets • Translate business questions into structured data models • Iterate quickly and improve outputs over time • Ship usable results fast, not perfect results slowly