Data Scientist II - Experimentation

$109,200 - $202,800/Yr

Spectrum - New York, NY

Full-time - Mid Level

New York, NY

Telecommunications

About the position

As a Data Scientist II on the WBD Experimentation Data Science team, you will leverage large datasets to extract insights and guide decision-making throughout the product development lifecycle for the streaming platform, MAX. This role involves setting up best practices for experiment design and advanced analysis, collaborating with product stakeholders across various areas of the video streaming business to drive growth and enhance platform performance.

Responsibilities

• Support the design, monitor and deep dive analysis of A/B tests in various business settings.
• Work end to end with product stakeholders from idea initiation, experiment design/monitoring to sharing results analysis for decision making.
• Study and fully understand WBD data sources and develop metrics for measuring platform performance in A/B tests.
• Write efficient queries to pull data for KPIs and metrics to diagnose changes observed in experiments.
• Perform advanced statistical tests to real world A/B test datasets to measure impacts of new product features.
• Apply causal model to investigate cause-effect relationship between KPIs and key product changes.
• Perform research to acquire best in class data science techniques and best practices to improve the rigor and efficiency in product experimentation.
• Capture business requirements for data science solutions and communicate data science output and recommendations to inform business strategies.
• Present analysis to business partners and senior leadership and make product launch recommendations.

Requirements

• Experience in data science, particularly in A/B testing and experimentation.
• Strong statistical analysis skills and experience with statistical testing methods.
• Proficiency in SQL and experience with querying large datasets.
• Ability to communicate complex data insights to non-technical stakeholders.
• Experience with data visualization tools and techniques.

Nice-to-haves

• Familiarity with video streaming platforms and analytics.
• Experience with causal inference methods.
• Knowledge of machine learning techniques and their application in product development.

Benefits

• Health insurance coverage
• Employee wellness program
• Life and disability insurance
• Retirement savings plan
• Paid holidays
• Sick time
• Vacation