KAYAK, part of Booking Holdings (NASDAQ: BKNG), is the world’s leading travel search engine. With billions of queries across our platforms, we help people find their perfect flight, stay, rental car and vacation package. We’re also transforming business travel with a new corporate travel solution, KAYAK for Business.
As an employee of KAYAK, you will be part of a travel company that operates a portfolio of global metasearch brands including momondo, Cheapflights and HotelsCombined, among others. From start-up to industry leader, innovation is in our DNA and every employee has an opportunity to make their mark. Our focus is on building the best travel search engine to make it easier for everyone to experience the world.
The Marketing Measurement team's mission is to improve KAYAK's ability to measure the efficiency of marketing efforts. This role works closely with marketing leaders to make better data-informed strategic marketing decisions.
As a Senior Data Scientist on this team, you will have the opportunity to:
* Manage end-to-end experimentation from formulating hypotheses, experiment design to collecting the right data, performing power analysis, and analyzing experiment results.
* Support initiatives towards building a robust framework for efficiently creating and evaluating creative, bidding, and landing page experiments.
* Develop new models and advanced analytics techniques to measure and optimize marketing spend.
* Support the development of less senior scientists and collaborate with team members to ensure timely delivery of high-quality work.
* Build standardized and scalable solutions, leading by setting up best practices.
Please apply if you have:
* Advanced degree (Masters, PhD) in Data Science, Statistics, or a related field.
* Extensive experience with data manipulation and extraction using relational databases (SQL).
* Ability to write high-quality, scalable, maintainable code (Python, R).
* Strong story-telling and presentation skills to communicate effectively with business partners, primarily within Marketing.
* Strong foundation in experimentation methods and causal inference techniques.
* Experience in marketing science measurement methodologies like causal impact, geo-lift on Google, and marketing mix models.
* Proactive work style, needing minimal guidance and demonstrating good judgment.
* Keen sense of success criteria with a strong adherence to testing and validation principles.
* Passion for large data sets in marketing, finance, and economics, with skills in paid marketing data, time-series analysis, econometrics, and regression models.
Benefits:
* Work from (almost) anywhere for up to 20 days per year.
* Focus on mental health and well-being: Company-paid therapy sessions, subscription to HeadSpace, and a company-wide week off a year.
* No meeting Fridays.
* Paid parental leave.
* Generous paid vacation + time off for your birthday.
* Paid volunteer time.
* Focus on your career growth: Development Dollars, leadership development, access to thousands of on-demand e-learnings.
* Travel discounts.
* Employee Resource Groups.
* 5 weeks paid vacation.
* Social events & Thursday happy hours.
* Free lunch 2 days per week.
* Pension plan contributions.
* Supplemental accident insurance.
* Health insurance subsidy of 250 CHF per month.
* Lunch Check Card of 180 CHF per month.
* Profawo membership to promote compatibility of family and work.
Diversity, Equity, and Inclusion
At OpenTable/KAYAK, we aspire to be a workplace that fosters inclusion and reflects the diverse communities we serve. Hiring people with different backgrounds and perspectives is critical to innovation and to how we deliver great experiences for our users, partners, and teams. We strive to be an open and welcoming environment so that no matter who you are, you can be yourself.
We ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform job responsibilities, and to receive other benefits and privileges of employment. Please contact us to request an accommodation(s).
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