Data Scientist 6 – Experimentation Platform

This is a fully remote position, open to applicants in United States.

📋 Description

• Assist in establishing the strategy for the Experimentation Platform, which includes user interface design and user workflows.

• Outline how data scientists can contribute metrics, reports, and templates to the platform.

• Ensure that the Experimentation Platform allocates, logs, and processes data utilizing reliable and valid causal inference methods.

• Convert verification into an automated, repeatable, and monitored procedure.

• Serve as a strategic collaborator for data science and engineering stakeholders throughout Netflix.

• Link data science requirements with the implementation of platform engineering.

• Advocate for the needs of the Data Science organization directly to engineering leadership.

• Influence and advance large-scale experimentation across Netflix.

• Establish standards for inference practices, including peeking, covariate adjustment, anytime valid methods, metric definitions, and allocation mechanisms.

• Promote the adoption of experimentation practices among data science teams.

• Lead the integration of fragmented experimentation systems into a unified and maintainable platform.

• Create tools and processes to ensure that best practices are the easiest path to follow.

• Mentor team members engaged with the platform.

• Represent the Experimentation Platform’s perspective in company-wide discussions regarding experimentation methodology.

⛳️ Requirements

• An advanced degree (PhD or Masters) in Computer Science, Statistics, Economics, Applied Mathematics, or a related quantitative discipline.

• Over 8 years of experience with statistics and causal inference in an experimentation context, including designing scalable experiments and troubleshooting failures.

• A proven record of establishing standards or creating tools that are adopted across multiple teams or across the entire organization.

• Extensive, practical understanding of experimentation challenges, such as sample ratio mismatches, winner's curse, regression to the mean, false discovery rates across a portfolio of tests, peeking, covariate adjustments, and allocation versus analysis unit discrepancies.

• Experience in translating vague data science challenges into a structured product roadmap.

• At least 5 years of experience with data science programming languages, preferably including Python and SQL.

• Ability to work closely with engineers on API, schema, and system design.

• Excellent communication skills across functions and the ability to influence both technical and non-technical stakeholders.

• A strong desire to learn new statistical methods and optimization techniques.

• The discernment to recognize when established methods are the preferred choice.

🏝️ Benefits

• Comprehensive Health Plans.

• Support for Mental Health.

• 401(k) Retirement Plan with employer matching contributions.

• Stock Option Program.

• Disability Programs.

• Health Savings and Flexible Spending Accounts.

• Family-forming benefits.

• Life and Serious Injury Benefits.

• Paid leave of absence programs.

• Full-time hourly employees earn 35 days annually for paid time off for vacation, holidays, and sick leave.

• Full-time salaried employees are immediately eligible for flexible time off.