> Markdown version of [/jobs/ext/4573613-data-team-lead-lead-data-scientist](https://www.wearedevelopers.com/jobs/ext/4573613-data-team-lead-lead-data-scientist). 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).

---

# Data Team Lead / Lead Data Scientist

- **Company:** Harnham Bekijk Alle Vacatures
- **Location:** Amsterdam, Netherlands
- **Experience:** Expert
- **Salary:** €5,833.0 - €8,333.0
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Airflow, Data Analysis, Computing Platforms, BigQuery, Data Governance, Data Transformation, Data Systems, Decision Support Systems, Dimensional Modeling, Machine Learning, Recommender Systems, Workflow Management Systems, Data Management
- **Published:** November 5, 2026
- **Apply:** https://www.careerjet.nl/job/nlb1292b797a5c761e982722f58ff3a6f3/eaa

## About the Role

Your Skills & Experience You will bring a blend of platform expertise, machine learning capability, and leadership potential.
Key requirements include:

 * Strong experience designing and operating modern cloud data platforms
 * Hands-on expertise with dbt and data transformation best practices
 * Experience with orchestration tools such as Airflow
 * Strong knowledge of data modelling, including dimensional modelling approaches
 * Experience working with GCP and BigQuery
 * Proven capability deploying machine learning or statistical models into production environments
 * Experience with experimentation frameworks and A/B testing
 * Knowledge of recommendation systems or ranking models
 * Ability to communicate effectively with technical and commercial stakeholders
 * Leadership experience or a demonstrated ability to guide and influence teams
 * Based in the Netherlands or willing to relocate

Desirable experience:

 * E-commerce, marketplace, travel, or other high-volume digital environments
 * Building or scaling data teams and platform capabilities
 * Analytics engineering and self-service BI initiatives
 * Platform architecture and data governance leadership

## Description

Data Team Lead / Lead Data Scientist Amsterdam, Netherlands (Hybrid) | €85,000 - €110,000 including holiday allowance
This is an opportunity to take ownership of a growing data function at a business that has already invested heavily in its data foundations and is now entering the next phase of maturity. You'll combine technical leadership with hands-on delivery, shaping both the platform and the future direction of data products that directly influence commercial performance.
The Company They are a well-established consumer-focused organisation with a strong digital presence and a growing commitment to data-driven decision making. Following significant investment in their data capabilities, they have built modern foundations and are now looking for someone to lead the next stage of development.
Working in a collaborative environment, you'll partner closely with technology, product, and commercial stakeholders to deliver measurable business impact through analytics, machine learning, and platform innovation.
The Role As a Data Team Lead / Lead Data Scientist, you will be responsible for driving the evolution of the organisation's data platform while remaining deeply involved in technical delivery.
Key responsibilities include:

 * Taking ownership of the data platform and its ongoing development
 * Leading the design and operation of modern cloud-based data solutions
 * Introducing and improving model lifecycle management, monitoring, and governance practices
 * Building scalable capabilities across analytics, machine learning, and self-service BI
 * Driving initiatives across areas such as recommendation systems, search optimisation, experimentation, and commercial analytics
 * Partnering with product and business stakeholders to define success metrics and prioritise opportunities
 * Supporting the growth and development of the data team
 * Balancing strategic leadership with hands-on technical contributions across data and machine learning projects