• Design, develop, and productionize machine learning (ML) solutions in the fields of Document understanding, Search and QnA, GenAI, Virtual Agents, etc. • Develop and maintain backend services using Python, focusing on AI-driven applications. • Design and implement APIs for seamless integration with AI models and services. • Collaborate with product managers, engineers, and other stakeholders as a specialist and subject matter expert in machine learning. • Work across the complete lifecycle of ML model development, including problem definition, data exploration, feature engineering, model training, validation, and deployment. • Participate in code reviews, testing, and quality assurance processes. • Troubleshoot and resolve technical issues related to AI model, integration, deployment and backend services. • Implement system telemetry, A/B testing and other statistical methods to validate the effectiveness of AI models. Ensure the integrity and robustness of ML solutions by developing automated testing and validation processes. • Document and communicate development processes, system designs, and architectural decisions. • Ensure the security and compliance of healthcare data, adhering to HIPAA regulations. • Responsible for adherence to the Capital Rx Code of Conduct, including reporting of noncompliance.

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. In April 2022, we announced that we are creating a new lower-priced, ad-supported tier for our customers. We are now working toward our goal of providing more choice for consumers and a premium, better-than-linear TV brand experience for advertisers. We are now hiring for the founding data scientists in this fast evolving business area for Netflix! Our goal in the Ads Audience & Identity Science team is to deepen our understanding of our ad-tier members, in order to improve advertiser performance and ensure a great member experience. We continually improve ad targeting capabilities through identity modeling, machine learning, analytics, data exploration, and optimization. Our work includes feature engineering, modeling, lookalike algorithms, and optimization. We also provide modeling and analytics support for Netflix live content and integrations with third-party partners, with a high priority on privacy and data security. We focus on repeatable, scalable modeling for a variety of current and future applications. This role is for a Machine Learning Scientist (L5) to focus identity modeling for our ads member base, including identity modeling, probabilistic matching, graph analytics, differential privacy, anonymization, and identity metrics. Responsibilities - ​​Apply modeling and machine learning techniques to business problems at the intersection of product and data science - Autonomously identify and pursue research with significant business impact, and make compelling cases for prioritization and resource allocation - Diagnose data and model assumptions, curating and testing appropriate models for each dataset and business objective - Identify, compute and validate the appropriate metrics to measure success - Deliver well-documented datasets, tools, and reports to key technical and business partners - Serve as a strategic thought partner to product managers and business stakeholders, directly influencing product direction and improving user experience. - Cultivate strong partnerships with cross-functional stakeholders from product, engineering, operations, design, consumer research, etc. - Effectively communicate findings and insights to both technical and non-technical audiences, driving adoption and understanding of ML-driven solutions. Qualifications - Advanced degree (PhD or Master’s) in Computer Science, Statistics, Economics, Applied Mathematics, or related quantitative field - 5+ years of experience and high proficiency in SQL, Python; 5+ years of experience with large scale data - Deep knowledge of machine learning, statistics, optimization, and data analysis techniques - Experience in identity graphs, privacy, differential privacy, anonymization and identity-related concepts - Strong business acumen and ability to translate technical results into business impact - Excellent communication and collaboration skills - Comfortable with ambiguity; able to thrive with minimal oversight and process - Prior experience in ad tech, streaming, technology, or consumer-facing products is a plus. 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 $466,000.00 - $750,000.00. 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.

• Designs and develops scalable solutions using AI tools and machine-learning models • Performs research and testing to develop machine learning algorithms and predictive models • Utilizes big data computation and storage tools to create prototypes and datasets • Conducts model training and evaluation • Integrates, tests, tunes, and monitors solutions • Leads the design, development, and research around complex Machine Learning (ML) systems, models, and schemes to apply to appropriate datasets for data modeling and statistical analysis • Identifies differences in data distribution that could affect model performance in real-world situations • Analyzes large and complex use cases of ML algorithms and apply findings to enable business decisions by deriving insights through data visualization • Leads the maintenance and support of ML/AI software platforms by reviewing and solving issues and running ML/AI models • Communicates business objectives and develop complex models that help to achieve them, along with metrics to track their progress • Leads the writing of complex software documentation and complex software code to extract data from a variety of databases and data sources • Manages available resources such as hardware, data, and personnel so that deadlines are met and deploy predictive models using established software patterns • Leads the analysis of the ML algorithms that could be used to solve a given problem and rank them by their success probability • Explores and visualizes data to gain an understanding of it and verify data quality, and/or ensure data quality via data cleaning • Analyzes errors of the model and implements strategies to overcome errors

• contribute to designing, scaling/building, evaluating, integrating, shipping, and refining reward signals for recommendations by hands-on ML development • promote and role-model best practices of ML systems development, testing, evaluation • lead collaborations and align across PZN to integrate and A/B test mid-term signals in various recommendation systems