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.
In 2022, we announced that we are creating a new lower-priced, ad-supported tier for our customers. Since then, we have been working toward our goal of providing more choice for consumers and a premium, better-than-linear TV brand experience for advertisers. That said, we are looking for the founding members of this budding business area for Netflix!
The Media Planning and Recommendation team in Ads DSE at Netflix’s mission is to help build an industry-leading media planning suite for the success of Netflix’ the ads business. We conduct analyses and build Machine Learning models and algorithms in product and targeting recommendation, all with the ultimate goal of creating more choices and joy for our members. As a tech leader in this space, you will work closely with partner teams in Product and Engineering to think big about our business goals and draw the blueprint for how we can achieve them through models and algorithms. You will research the problem and find and build the most appropriate solution from an ensemble of ML techniques, applying strong analytical and science rigor. You will collaborate efficiently with partners in Engineering, Product, and Design in this 0 - 1 space for the ultimate success of Netflix Ads.
Develop, prototype, and iterate on machine learning models and optimization algorithms to address core business challenges in advertising.
Deploy models using production-scale data, focusing on robust offline solutions that inform real-world business decisions.
Apply a broad range of modeling techniques (e.g., machine learning, statistics, optimization) and model assessment strategies (e.g., cross-validation, resampling, dimensionality reduction, feature selection).
Diagnose data and model assumptions, curating and testing appropriate models for each dataset and business objective.
Translate complex model outputs into actionable metrics and KPIs for non-technical stakeholders, ensuring clarity and business alignment.
Serve as a strategic thought partner to product managers and business stakeholders, directly influencing product direction and improving user experience.
Effectively communicate findings and insights to both technical and non-technical audiences, driving adoption and understanding of ML-driven solutions.
Advanced degree (PhD or Master’s) in Computer Science, Statistics, Mathematics, or related quantitative field.
Proficiency in Python or Scala.
Deep knowledge of machine learning, statistical modeling, and data analysis techniques.
Experience with prototyping and deploying models using large-scale production data.
Strong business acumen and ability to translate technical results into business impact.
Experience in building ad ranking or recommendation or optimisation models.
Excellent communication and collaboration skills.
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 $150,000 - $750,000.
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.