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KAYAK

Marketing Data Science Manager

Cambridge OfficeUnited Kingdom
Manager · FullTime · Cost Centers
POSTED 2 NOVVERIFIED 3H AGO
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Open for
1d
since 2 Nov
H-1B · FY26
8
certified LCAs
Hiring · 30d
45
0 net · open roles

KAYAK, part of Booking Holdings (NASDAQ: BKNG), is a 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.

KAYAK is seeking a Data Science Manager to lead our Marketing Data Science team. The team builds the models, experimentation frameworks, and measurement systems that guide how we invest our global marketing spend, and the insights that show what is working across SEM, SEO, brand, and the wider marketing organization.

Marketing is central to KAYAK's growth strategy. In this role you will manage a team of data scientists and set the technical direction for marketing measurement, experimentation, and advanced analytics. You will stay hands-on in key projects while building a trusted team, and you will partner with colleagues across marketing, technology, and business teams to turn analysis into decisions that drive efficient growth.

What your team covers

Marketing measurement: attribution, marketing mix modeling, incrementality and geo-lift testing, value estimation, and user LTV

Experimentation: the end-to-end marketing experimentation lifecycle, from test design and power analysis to execution, analysis, and readouts

Brand media measurement: measuring the impact of upper-funnel and brand investment on traffic, conversion, and long-term value

User journey and landing page analytics: understanding how users move from acquisition to conversion, and identifying funnel and landing page improvements

SEO analytics and measurement: quantifying organic performance and the incremental value of SEO initiatives

PPC analytics: supporting paid search optimization, including performance diagnostics, bidding and budget allocation, and forecasting

In this role you will

Lead, coach, and develop a team of data scientists — setting goals, supporting each person's career growth, and creating an environment where curiosity and ownership are the norm

Set the team's roadmap and priorities in line with company goals, focusing on the work with the most impact across SEM, SEO, brand, and other channels

Own the marketing experimentation process and set standards for test design, statistical rigor, and decision-making

Lead the development of measurement frameworks that combine marketing mix modeling, attribution, and incrementality testing into a coherent view of channel and brand effectiveness

Oversee analytics for paid search, SEO, brand media, and user journey and landing page performance — and turn that analysis into clear recommendations on budget allocation, channel strategy, and test priorities

Partner with data engineering, machine learning, and software engineering teams to build scalable, reusable data products

Stay hands-on in the most important technical work, including modeling, analysis, and code review, while gradually shifting time toward team leadership

Keep the team ahead of changes in data privacy, marketing platform measurement, and AI-driven search and advertising

Please apply if you have

Experience leading or mentoring data scientists or analysts in a team setting, with a track record of helping people grow and do their best work

Hands-on experience with statistical inference, experimentation, and causal inference — including A/B testing, geo experiments, and incrementality measurement

Experience with marketing measurement methods such as marketing mix modeling, attribution, and LTV modeling

Experience in analytics for at least one of paid search/PPC, SEO, or brand/upper-funnel media, and the curiosity to build depth across the others

Source · KAYAKFirst seen 2 NovOriginal ↗