Data Science Manager

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 looking for a Data Science Manager to lead the Concord-based data science team. This is a senior, hands-on leadership role.

You’ll lead experienced Data Scientists, set technical direction, make key architecture decisions, and get directly involved in solving the hardest modeling and experimentation problems. The teams owns applied Data Science for AdTech, auctions and the company-wide shared experimentation platform. You will work closely with Product, Engineering, and business partners to align priorities and build scalable, measurable solutions that improve decision-making across KAYAK.

If you’re excited to lead strong Data Science teams and build the capabilities that help KAYAK test ideas and make better decisions, we’d love to hear from you.

What you’ll do

• Own the strategy and roadmaps for AdTech/Auction and KAYAK’s shared Experimentation Platform, aligning priorities with business objectives and long-term technical direction.
• Lead, mentor, and grow a high-performing team of experienced Data Scientists based in Concord, fostering technical excellence, autonomy, and accountability.
• Drive technical direction across modeling, experimentation, and ML solutions, providing guidance and contributing hands-on where it creates the greatest impact.
• Evolve and simplify the Experimentation Platform, ensuring scalable shared capabilities and clear ownership boundaries between platform infrastructure and use-case-specific logic.
• Turn business challenges into measurable outcomes, guiding the development, evaluation, and productionization of ML solutions that improve user experience and business performance.
• Champion rigorous experimentation and data-driven decision-making, ensuring reliable results, actionable insights, and continuous improvement.
• Collaborate across Data Science, Product, Engineering, and Operations, aligning stakeholders, managing dependencies, and driving complex initiatives from concept to production.

What you’ll bring

• Strong technical foundations in statistics, machine learning, software engineering, and systems design, backed by a track record of solving complex, real-world problems. Demonstrated capability matters more than academic credentials.
• Demonstrated experience delivering impactful ML solutions in production environments, with a clear understanding of the technical decisions, trade-offs, and business outcomes involved.
• Meaningful people leadership experience, including hiring, coaching, performance management, and developing experienced technical talent, while maintaining a high technical bar and contributing hands-on where it matters most.
• Ability to lead across organizational boundaries, building alignment, navigating competing priorities, and driving outcomes through collaboration rather than authority.
• Strong ownership, judgment, and systems thinking, with the ability to navigate technical, cost, reliability, and risk trade-offs and influence senior stakeholders.
• Fluency with AI-assisted workflows, leveraging modern tools to improve productivity and quality while critically evaluating their outputs and limitations.
• Curiosity, humility, and a collaborative mindset, with a commitment to continuous improvement and the ability to inspire the same in others.
• Bonus qualifications
• Hands-on experience with technologies relevant to KAYAK’s stack, such as PyTorch, Polars, CometML, Arize, Docker, Airflow, Trino and Git/Github.
• Familiarity with Agile ways of working, such as sprint planning and team ceremonies.