Netflix : Data Scientist (L5) - Content Promotion & Discovery Performance

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Overview

Netflix is seeking a Senior Data Scientist (L5) for their Content Promotion & Discovery Performance team. This role is remote and open to applicants from anywhere in the world, with headquarters based in California. The primary focus of the position is to enhance member engagement by optimizing how Netflix distributes and promotes its content, utilizing a blend of statistical analyses and machine learning techniques.

Role Responsibilities

As a Senior Data Scientist, your mission will involve:

• Leveraging causal inference methods or statistically sound analyses to generate actionable insights, aiding in the understanding of how product features, content, and algorithms shape members' content discovery.
• Developing metrics and measurement frameworks that are robust in both statistical and causal perspectives. This helps stakeholders make informed decisions regarding product features aimed at increasing member satisfaction.
• Establishing collaborative relationships with various stakeholders, covering business leaders, engineering teams, and diverse departments within Netflix.
• Ensuring that the team produces high-quality outputs that influence decisions across Netflix’s multitude of operational facets.
• Proactively exploring trends in content discovery to identify future opportunities for engagement and member joy.
• Working independently and managing your own projects while contributing to team goals.

Required Skills and Qualifications

Candidates interested in this role should possess the following attributes:

• A master’s degree or higher in a relevant quantitative field such as Statistics, Mathematics, Computer Science, or Economics.
• 5+ years of experience in data science or related roles, with a focus on statistical analysis.
• Strong communication skills that effectively relay information between technical teams and non-technical audiences; abilities to nurture deep relationships with stakeholders.
• Proficient knowledge in statistical analysis methods, particularly in causal inference and statistical learning.
• Robust quantitative programming skills, especially in Python, along with expertise in SQL for data manipulation.
• Ability to work in uncertain environments, demonstrating flexibility and independence.

Compensation and Benefits

The compensation structure for the position consists strictly of an annual salary with no bonuses. Candidates have the flexibility to choose how their compensation is allocated between salary and stock options each year. The salary range for this role is between $372,000 and $600,000, with adjustments based on location and individual qualifications.

Netflix offers a comprehensive benefits package that includes:

• Health Plans and Mental Health support.
• A 401(k) retirement plan with employer matching.
• Stock Option Program.
• Disability Programs, Health Savings Accounts, and Flexible Spending Accounts.
• Family-forming benefits and paid leave of absence programs.
• For full-time hourly employees, accrual of 35 days annually for paid time off, including vacation, holidays, and sick days, while salaried employees are entitled to immediate flexible time off.

Culture and Inclusion

Netflix pride itself on its unique culture that emphasizes diversity and inclusion. They are committed to providing fair and thoughtful treatment to all candidates in the hiring process. Accommodations are available upon request for candidates with disabilities.

Application Process

The job will remain open for a minimum of 7 days and may be removed once filled. Interested applicants can apply through the official Netflix careers page.

Conclusion

This role presents a remarkable opportunity for experienced data scientists to contribute to an innovative team and be a part of Netflix's ongoing success in delivering tailored content to its global audience. With a strong focus on analytics, causal inference, and statistical methods, the position requires a strategic thinker equipped with top-notch skills in data science.

This job offer was originally published on weworkremotely.com