Marketing Data Science Manager

allocation, and forecastingIn 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 normSet 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 channelsOwn the marketing experimentation process and set standards for test design, statistical rigor, and decision-makingLead the development of measurement frameworks that combine marketing mix modeling, attribution, and incrementality testing into a coherent view of channel and brand effectivenessOversee 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 prioritiesPartner with data engineering, machine learning, and software engineering teams to build scalable, reusable data

productsStay hands-on in the most important technical work, including modeling, analysis, and code review, while gradually shifting time toward team leadershipKeep the team ahead of changes in data privacy, marketing platform measurement, and AI-driven search and advertisingPlease 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 workHands-on experience with statistical inference, experimentation, and causal inference - including A/B testing, geo experiments, and incrementality measurementExperience with marketing measurement methods such as marketing mix modeling, attribution, and LTV modelingExperience in analytics for at least one of paid search/PPC, SEO, or brand/upper-funnel media, and the curiosity to build depth across the othersStrong Python and SQL skills, with experience building and deploying models in a production or near-production environmentThe ability to communicate technical work clearly to marketing, product, and business partners who may not have a data science backgroundA collaborative, non-hierarchical, and humble leadership styleNice to have:Experience with econometric modeling, Bayesian methods, or causal modelingFamiliarity with web analytics and user journey or funnel analysisExperience in online travel, e-commerce, or another performance-marketing-driven businessFamiliarity with open-source marketing mix modeling tools (e.g., Meridian, Robyn, PyMC-Marketing)Experience measuring traffic from AI search and LLM-driven channelsA note on qualifications: We have intentionally not listed a required degree field or a minimum number of years of experience. We value demonstrated skills, curiosity, and impact over credentials. Candidates from non-traditional backgrounds - including those who are self-taught, have taken non-linear career paths, or are returning to the workforce - are warmly encouraged to apply.Benefits and PerksWork from (almost) anywhere for up to 20 days per yearFocus on mental health and well-being:Company-paid therapy sessions through SpringHealthCompany-paid subscription to HeadSpaceCompany-wide week off a year - the whole team fully recharges (and returns without a pile-up of work!)No meeting FridaysPaid parental leaveGenerous paid vacation + time off for your birthdayPaid volunteer timeFocus on your career growth:Development DollarsLeadership developmentAccess to thousands of on-demand e-learningsTravel DiscountsEmployee Resource GroupsCompetitive retirement and health plansFree lunch 2 days per weekFun quarterly events such as boat trips, arcades, ski trips, Thursday happy hours, and moreCOMPENSATION There are a variety of factors that go into determining a salary range, including but not limited to external market benchmark data, geographic location, and years of experience sought/required.

The range for this Massachusetts based role is $160,000 - $200,000, not inclusive of annual bonus and recurring RSU grants.We offer a competitive base salary and benefits including: health benefits; flexible spending account; retirement benefits; life insurance; paid time off (including PTO, paid sick leave, medical leave, bereavement leave, floating holidays and paid holidays); and parental leave benefits.INCLUSION At KAYAK, we want everyone to have the space to grow, share ideas and do great work. That’s why we’re focused on hiring the best talent from all walks of life and experiences, supporting them well and making sure no one feels like they have to fit a mold to belong here.Need any adjustments for the interview, application or on the job? No problem - just give us a heads-up.

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 coversMarketing measurement: attribution, marketing mix modeling, incrementality and geo-lift testing, value estimation, and user LTVExperimentation: the end-to-end marketing experimentation lifecycle, from test design and power analysis to execution, analysis, and readoutsBrand media measurement: measuring the impact of upper-funnel and brand investment on traffic, conversion, and long-term valueUser journey and landing page analytics: understanding how users move from acquisition to conversion, and identifying funnel and landing page improvementsSEO analytics and measurement: quantifying organic performance and the incremental value of SEO initiativesPPC analytics: supporting paid search optimization, including performance diagnostics, bidding and budget