> Markdown version of [/jobs/ext/4539909-marketing-data-science-manager](https://www.wearedevelopers.com/jobs/ext/4539909-marketing-data-science-manager). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Marketing Data Science Manager

- **Company:** Kayak Software Corporation
- **Location:** Cambridge, United States
- **Salary:** $160,000.0 - $200,000.0
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Artificial Intelligence, Code Review, Information Engineering, Python (Programming Language), Machine Learning, Open Source Technology, Standard Sql, Search Technologies, Software Engineering, Web Analytics, Large Language Models, Power Analysis (Cryptography), Machine Learning Operations
- **Published:** November 3, 2026
- **Apply:** https://startup.jobs/marketing-data-science-manager-kayak-com-10658617

## About the Role

* 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
 * Strong Python and SQL skills, with experience building and deploying models in a production or near-production environment
 * The ability to communicate technical work clearly to marketing, product, and business partners who may not have a data science background
 * A collaborative, non-hierarchical, and humble leadership style

Nice to have:

 * Experience with econometric modeling, Bayesian methods, or causal modeling
 * Familiarity with web analytics and user journey or funnel analysis
 * Experience in online travel, e-commerce, or another performance-marketing-driven business
 * Familiarity with open-source marketing mix modeling tools (e.g., Meridian, Robyn, PyMC-Marketing)
 * Experience measuring traffic from AI search and LLM-driven channels

A 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.

## Description

* 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