Netflix

Netflix is one of the world's leading entertainment services, with 283 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.

Data is at the heart of our payment strategy and innovation at Netflix. In the Payments Data Science & Engineering team, we provide guidance to the business not only through analysis, metrics research, experimentation, causal inference, and modeling, but also through exceptional judgment, partnership, and business acumen. Our team’s portfolio includes production ML models that we maintain and innovate upon, as well as zero-to-one efforts in greenfield application spaces. These deeply collaborative, innovative efforts unlock millions of dollars of revenue impact each year.

As a Senior Machine Learning Scientist, you will join this team of stunning Data Scientists, Analytics Engineers, and Research Engineers. You’ll lead the development of ML models that improve member experience and efficiency for billions of payments transactions each year and stop fraud in real-time.

In this role, you will:

• Own and innovate on our suite of payment models, such as real-time fraud detection and optimization
• Have end-to-end ownership of ML model development lifecycle, from ideation and feature engineering, to model training, evaluation, deployment and continuous monitoring and improvement.
• Partner closely with Payment leads and analysts to identify high-value applications of machine learning, translating business intuition into data-driven solutions 
• Partner with data scientists on model performance evaluation and A/B testing
• Inform and influence the development of better infrastructure for developing and deploying ML models in partnership with engineering, machine learning platform, and growth data science teams
• Live Netflix values while bringing a new perspective to continue improving our culture.

To be successful in this role, you have:

• Deep experience developing and deploying Machine Learning models with a successful track record of and passion for delivering business impact.
• Exceptional thought partnership and communication skills, able to explain complex technical concepts clearly to cross-functional partners 
• Ability to deal with ambiguity; a strong ownership mindset, and a desire to thrive on minimal oversight and process
• Deep familiarity with the ML lifecycle and strong technical judgment when assessing different solutions for deploying models in production.
• Willingness to learn and rapidly absorb business context in the complex payments ecosystem; payments domain experience a bonus
• Strong experience in Python and a ML/DL framework (e.g., scikit-learn, Keras, PyTorch, TensorFlow)
• An advanced degree (MS or PhD) in Computer Science, Electrical Engineering, Statistics, Computational Social Science, or a related technical field with a focus on machine learning, artificial intelligence, and predictive modeling.
• 4+ years of relevant experience in one or more machine learning roles

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 $360,000 - $920,000.

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.