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. When a Netflix member opens our app, we have a few precious moments to help them choose a story or a game that is right for them at that instance. Presenting them with evidence – Artwork, Trailers, Synopses – that authentically represent each title and resonate with the member is essential to this effort. Beyond connecting global stories with existing audiences, we also aim to reach new subscribers and increase engagement through innovative marketing campaigns. By crafting compelling and targeted marketing strategies, we strive to capture the attention of potential members and convert their interest into subscriptions. Additionally, we focus on increasing conversation and excitement about Netflix and our content, creating buzz and anticipation that encourages both current and prospective members to explore and engage with our diverse offerings. The Promotional Media AI for Member Systems team is at the forefront of designing and advancing state-of-the-art ML recommendation algorithms related to the "life of an asset" — spanning on-service promotional assets like artwork, synopses, and clips, as well as off-service marketing campaigns. We are responsible for empowering our business partners across Promotional Media and Marketing to understand, generate, and optimize these assets to provide a stellar member experience and drive subscriber growth. We are looking for an experienced Analytics Engineer to join our growing team. In this role, you will design and develop analytic tools and systems to monitor the adoption and accountability of our algos across both Promotional Media and Marketing workflows. You will partner with a talented cross-functional team of ML engineers, data scientists, product managers, and domain experts to shape the future of promotional asset recommendation and generation, as well as marketing campaign performance, at Netflix. Responsibilities Act as a strategic partner for stakeholders and cross-functional collaborators to identify analytic opportunities and enhance business strategies with automated data solutions Drive the direction and execution of your work, which spans from developing scrappy code to designing high-visibility dashboards and analyses Translate ambiguous creative and quality requirements into measurable objectives and evaluation frameworks Build and maintain observability for our automated pipelines, tracking SLA adherence, performance drift, and other key health signals to confirm our systems are performing as intended Partner closely with machine learning engineers and scientists to improve our asset creation and recommendation models, and accelerate the productization of data insights Share your innovation and collaborate with the broader analytics community to strengthen analytics enablement Become a knowledgeable practitioner/expert in our space, both as the go-to person regarding tooling and methodologies, and as a liaison with the stakeholders, understanding their business needs and how to fulfill them About you Proven track record of designing and developing scalable analytic tools and systems High proficiency in standard tech stack (e.g., Python, SQL, Spark) and common data visualization tools (e.g., Plotly Dash, Tableau) Familiar with the fundamentals of Statistical Inference and Data Analysis, as well as data engineering best practices 5+ years of relevant experience in building data products powered by big data Experienced in orchestrating cross-functional stakeholders without direct authority, and leveraging analytics to steer business decisions Exceptional communication and collaboration skills coupled with strong business acumen Comfortable with ambiguity; able to take ownership, and thrive with minimal oversight and process Netflix culture resonates with you Bonus points if experienced with pipelines and visualizations involving media files (images and video) 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.
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