Tripadvisor

Data Scientist II - Causal Inference

Remote Lisbon, Portugal
Machine Learning Python R
Description

We believe that we are better together, and at Tripadvisor we welcome you for who you are. Our workplace is for everyone, as is our people powered platform. At Tripadvisor, we want you to bring your unique identities, abilities, and experiences, so we can collectively revolutionize travel and together find the good out there.

 

At TripAdvisor, we never stop learning. This is true both individually and as a company, where constant experimentation helps us to understand how we can continue to grow and improve the user experience for our 500 million unique monthly visitors worldwide. Data-driven decision making is at the core of what we do.

 

About Data Science at Tripadvisor

Tripadvisor is the web's leading travel information site. At Tripadvisor, the ML Team creates systems that influence the travel decisions of millions of people per day. We apply cutting edge machine learning techniques to a wide variety of areas, including recommenders, online advertising, vision, text processing, and natural language processing. To ensure continued success, Tripadvisor promotes a culture of personal development, including social activities, journal clubs, memberships in online learning resources, and participation in industry conferences. Have a great time while shaping the future of travel!

 

About the role

We are looking for an experienced data scientist/statistician to join our Data Science/Machine Learning team.  As a Data Scientist focusing on Inference, you will be responsible for developing and implementing best practices in the design of experiments, A/B testing, the analysis of observational data, panel data analysis, time-series modeling, and more. In particular, you will be involved in marketing projects or other initiatives where traditional testing is not possible and non standard testing solutions are necessary. You will 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. Your work will contribute to the testing culture and will help determine which features and enhancements we deploy online, allowing you to directly observe the impact of your work in real time as you help the company grow.

 

What you'll do

We are looking for someone who is a fast learner, independent, and curious, who is passionate about data science and statistics. You will be working in a diverse environment where you’ll operate at the intersection of Data Science, Analytics, and Product. You will be encouraged to take ownership of your projects and to find new opportunities and problems where experimentation could be applied to drive the business forward. Additionally, you will be responsible for staying up to date on the literature, keeping up with state-of-the-art statistical research and methodology.

 

Skills & Experience

  • 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.

  • Experience with advanced machine learning methods a plus.

  • Experience working with real-world data strongly preferred.

  • Previous industry experience a plus.

 

We strive to create an accessible and inclusive experience for all candidates. If you need a reasonable accommodation during the application or the recruiting process, please make sure to reach out to your individual recruiter or our team at recruitment@tripadvisor.com 

 

 

 

#LI-GW1

#LI-REMOTE

#REMOTE

 

Tripadvisor
Tripadvisor
E-Commerce Hospitality Hotel Information Services Internet Restaurants Social Media Travel Vacation Rental

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