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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.

The Media AI Solutions Data Science and Engineering team is at the forefront of designing and advancing state-of-the-art ML recommendation algorithms related to the “life of an asset”, such as marketing campaigns, artwork, and clips. We are responsible for empowering our business partners to understand and generate these stunning Promotional Assets on our platform to provide a stellar member experience.

EMEA is a significant center for our broader Studio and Creative Production teams. We are looking for an experienced Analytics Engineer based in our Amsterdam office to join our growing EMEA team. In this role, you will design and develop analytic tools and systems to monitor the adoption and accountability of our algos . 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 at Netflix.

Responsibilities

• Act as 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 span from developing scrappy code to designing high-visibility dashboards and analyses

• Partner closely with machine learning engineers and scientists to improve our asset creation and recommendation models and accelerate productization of data insights

• Share your innovation and collaborate with the broader analytics community to strengthen analytics enablement

• Become a knowledgeable practitioner / expert on Media AI Solutions Data Science and Engineering, both as the go-to person regarding tooling and methodologies, and as a liaison with the creative 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 fundamentals of Statistical Inference and Data Analysis as well as data engineering best practices

• 5+ years of relevant experiences with building data products powered by big data

• Experienced 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)

Netflix culture

Netflix's culture is an integral part of what makes us successful, and we approach diversity and inclusion seriously and thoughtfully. We are an equal opportunity employer and celebrate diversity, recognizing that bringing together different perspectives and backgrounds helps build stronger teams. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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.