Machine Learning Scientist 5 - Localization

Netflix, Inc.; New York (NY); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Health Plans

Mental Health support

401(k) Retirement Plan with employer 5

Stock Option Program

Disability Programs

Health Savings

Flexible Spending Accounts

Family-forming benefits

Life and Serious Injury Benefits

paid leave of absence programs

Job summary

Netflix, Inc. in New York is seeking an experienced Machine Learning Scientist to join the Localization Data Science and Engineering team. You will build causal and ML models to evaluate localization impact and train supervised models for localization use cases.

You will partner with engineers, scientists, product managers, and domain experts to shape localization strategy and deliver measurable business impact in a fast-paced, collaborative environment.

Qualifications

• Proven track record researching and leading Causal Inference, Machine Learning, and AI Evaluation methods.
• High proficiency in standard tech stack (R, Python, SQL).
• 4+ years of relevant experience with Causal Inference and Machine Learning applications.
• Exceptional communication and collaboration skills with strong business acumen.
• Comfortable with ambiguity and able to take ownership with minimal oversight.

Responsibilities

• Act as strategic partner for researchers and engineers to guide localization algo development.
• Define and execute roadmaps for measuring localization impact and improving member experience using Causal Inference and ML tools.
• Partner with business leaders, product managers, and data scientists to refine and scale findings.
• Present research and insights to all levels of the company.
• Become a regional expert on Localization Data Science and Engineering.

Skills

R

Python

SQL

Causal Inference

Machine Learning

Communication

Job description

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 Localization Data Science and Engineering team is at the forefront of removing language barriers and providing a stellar member experience to all our members regardless of their language preferences. We are responsible for the translation and cultural adaptation of all aspects of member interaction, including beautiful localized user interfaces, subtitles, and dubbing of award‑winning Netflix originals. We are looking for an experienced Machine Learning Scientist to join our growing team. In this role, you will build causal and machine learning models to evaluate the impact of localization algos, partner with teammates to support localization algo strategy, and train supervised ML models for localization use cases. You will also partner with a talented cross‑functional team of engineers, scientists, product managers, and domain experts to shape localization strategy and deliver business impact.

Responsibilities

• Act as strategic partner for researchers and engineers to guide localization algo development
• Define and execute on roadmaps for measuring localization member impact and improving localization member experience with Causal Inference and Machine Learning tools
• Partner closely with other business leaders, product managers, and other data scientists to refine and scale your findings
• Present your research and insights to all levels of the company
• Become a regional expert on Localization Data Science and Engineering, helping educate and connect with regional offices

About you

• Proven track record of researching and leading Causal Inference, Machine Learning, and AI Evaluation methods in ambiguous and complex areas with a focus on technical rigor and robustness
• High proficiency in standard tech stack (e.g., R, Python, SQL), Causal Inference (e.g., propensity score matching, double machine learning), and Machine Learning (Supervised Learning, LLM Evaluation methods)
• 4+ years of relevant experience with Causal Inference and Machine Learning applications
• 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

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.

• Health Plans
• Mental Health support
• 401(k) Retirement Plan with employer match
• Stock Option Program
• Disability Programs
• Health Savings
• Flexible Spending Accounts
• Family-forming benefits
• Life and Serious Injury Benefits
• 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.

At Netflix, we want to entertain the world. Whatever your taste, and no matter where you live, we give you access to best‑in‑class TV series, documentaries, feature films and games. Our members control what they want to watch, when they want it, in one simple subscription. We’re streaming in more than 30 languages and 190 countries, because great stories can come from anywhere and be loved everywhere. We are the world’s biggest fans of entertainment, and we’re always looking to help you find your next favourite story.