[FULL TIME Remote] Data Science Manager - Engineering

Key Job Details:

• Start Date: Immediate openings available
• Compensation: a competitive salary
• Company: Workwarp
• Location: Remote
• Position: Data Science Manager - Engineering

 

 

Netflix is one of the world's leading entertainment services with 278 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 Role Netflix is a technical powerhouse, with infrastructure that powers a high performance, high reliability and high scale entertainment service. Our members want a seamless, immersive Netflix experience, and we deliver it with an intricate set of systems working together behind the scenes. Video and audio must be encoded into different formats and resolutions, distributed across our internally build content delivery network, then adaptively streamed by the wide range of devices our members use to watch the content they love. We have to do this all in cost effectively, securely, and nimbly. Our data team takes a holistic approach to measuring and improving... these systems and their impact on Netflix members as well as internal engineering teams. As we add new business areas like games, live content, and ads into the Netflix product, we're asking new questions about how our technology should work and how to best serve our members. What you'll do We're looking for an accomplished data science and analytics leader to lead a diverse team of talented, senior individual contributors who are experts in the fields of analytics, experimentation, and machine learning. You'll primarily partner with software engineering teams to optimize the Netflix streaming product with an eye toward scaling analytics, access to insights, innovating on methodologies, and finding new opportunities to apply high-impact science and analytics to Netflix challenges. You have • Experience hiring and leading high-caliber, data-focused teams with varying technical strengths across analytics, experimentation and machine learning • Experience creating and fostering an inclusive team culture • Experience partnering with technical engineering or product teams • Demonstrated strength for applying statistics and experimentation to solve problems • Strength in independently finding opportunities and executing on science and analytics challenges for maximum business impact 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. 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 detail about our Benefits here. Netflix is a unique culture and environment. Learn more here. We are an equal-opportunity employer and celebrate diversity, recognizing that diversity of thought and background 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 Apply Job!

 

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