Data Scientist II - Causal Inference

Summary

Join Tripadvisor's Data Science/Machine Learning team as an experienced data scientist/statistician focusing on Inference. You will develop and implement best practices in experimental design, A/B testing, and analysis of various data types. Collaboration with cross-functional teams is key to determining the best testing approaches across multiple initiatives and products. Your work will directly impact feature deployment and company growth. Tripadvisor promotes a culture of personal development with opportunities for professional growth. The role requires expertise in causal inference and time-series modeling, proficiency in Python or R, and excellent communication skills.

Requirements

• PhD in Statistics/Biostatistics, Economics, Mathematics, or related field (or masters with 2+ years of practical experience)
• Excellent communication skills for both technical and non-technical audiences
• Expertise in causal inference (propensity score methods, double ML, matching methods, etc.) and/or experimental/quasi-experimental design
• Experience with time-series modeling and analysis of repeated-measures data
• Proficiency in Python and/or R

Responsibilities

• Develop and implement best practices in the design of experiments
• Conduct A/B testing
• Analyze observational data
• Perform panel data analysis
• Develop time-series models
• Work on marketing projects or other initiatives where traditional testing is not possible and non-standard testing solutions are necessary
• Collaborate with data scientists, analysts, product managers, and engineers to determine the best course of action for testing and experimentation across a multitude of initiatives and products
• Contribute to the testing culture and help determine which features and enhancements we deploy online
• Stay up to date on the literature and keep up with state-of-the-art statistical research and methodology
• Take ownership of your projects and find new opportunities and problems where experimentation could be applied to drive the business forward

Preferred Qualifications

• Experience with advanced machine learning methods
• Experience working with real-world data
• Previous industry experience

Benefits

Culture of personal development, including social activities, journal clubs, memberships in online learning resources, and participation in industry conferences