Senior Data Scientist (m/f/d)

Jobgether; Netherlands; Hybrid; EUR 100,000 - 140,000; Full time

Benefits offered by this job

Direct collaboration with founders

Learning budget USD 1000

Home-office budget USD 500

Flexible work-from-home arrangement

Relocation to Berlin option

Job summary

Partner Company in the Netherlands seeks a Senior Data Scientist to build and improve machine-learning products operating at massive scale within the digital advertising ecosystem.

You will work with large, complex datasets and models processing billions of ad requests and users in real time, spanning research to production deployment and optimization.

Qualifications

• Minimum 5 years of professional experience developing data science or machine-learning products, ideally covering the full lifecycle from research through production deployment.
• Previous professional experience in Ad-Tech is required, with relevant exposure to programmatic advertising or mobile advertising technologies.
• Strong programming skills, particularly in Python, with a focus on clean, reproducible, maintainable, and well-tested code.
• Practical experience with technologies such as Spark, Hadoop, Airflow, Docker, and SQL.
• Hands-on experience developing algorithms for sparse and large-scale datasets, including prediction, clustering, and outlier detection.
• Experience building neural-network-based products for classification, regression, multi-task learning, or similar applications is highly valuable.

Responsibilities

• Develop, improve, and maintain machine-learning models used within large-scale programmatic advertising systems.
• Enhance existing models by introducing new features, tuning parameters, and incorporating additional data sources.
• Collaborate with Machine Learning Engineers to research, develop, and deploy scalable supervised and unsupervised learning algorithms.
• Explore new and existing data sources to identify opportunities for improving models and product performance.
• Design, run, and analyze A/B tests to validate hypotheses, measure impact, and guide product and modeling decisions.
• Develop solutions capable of handling sparse, large-scale datasets for prediction, clustering, outlier detection, and related use cases.
• Contribute to neural-network-based products for classification, regression, multi-task learning, and other relevant applications.
• Build clean, reproducible, well-tested code suitable for production environments.
• Develop and improve monitoring solutions, dashboards, and data-driven tools to track model and system performance.
• Work closely with analysts, engineers, and other data scientists to communicate findings and translate research into practical solutions.

Skills

Python

Spark

Hadoop

Airflow

SQL

Docker

Reinforcement learning

Neural networks

Experimentation

Communication

Tools

Spark

Hadoop

Airflow

Docker

SQL

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Scientist (m/f/d) based in Netherlands.

This role offers the opportunity to build and improve machine-learning products operating at exceptional scale within the digital advertising ecosystem.
You will work with large, complex datasets and models processing billions of ad requests and users in real time.
The position spans the full data science lifecycle, from research and experimentation through production deployment and continuous optimization.
You will collaborate closely with data scientists, analysts, and machine learning engineers to develop scalable solutions with measurable business impact.
Your work will directly contribute to improving product performance, customer outcomes, and the efficiency of programmatic advertising systems.
The environment is international, highly collaborative, experimentation-driven, and focused on solving complex problems with practical machine learning.
This is an opportunity for an experienced data scientist to work on challenging problems while having meaningful technical and commercial impact.

Accountabilities:

• Develop, improve, and maintain machine-learning models used within large-scale programmatic advertising systems.

• Enhance existing models by introducing new features, tuning parameters, and incorporating additional data sources.

• Collaborate with Machine Learning Engineers to research, develop, and deploy scalable supervised and unsupervised learning algorithms.

• Explore new and existing data sources to identify opportunities for improving models and product performance.

• Research and evaluate machine-learning approaches that can optimize different stages of the business and technology value chain.

• Design, run, and analyze A/B tests to validate hypotheses, measure impact, and guide product and modeling decisions.

• Develop solutions capable of handling sparse, large-scale datasets for prediction, clustering, outlier detection, and related use cases.

• Contribute to neural-network-based products for classification, regression, multi-task learning, and other relevant applications.

• Build clean, reproducible, well-tested code suitable for production environments.

• Develop and improve monitoring solutions, dashboards, and data-driven tools to track model and system performance.

• Work closely with analysts, engineers, and other data scientists to communicate findings and translate research into practical solutions.

• Maintain a strong focus on simplicity, experimentation, measurable impact, and solutions that address real business problems.

Requirements:

• Minimum 5 years of professional experience developing data science or machine-learning products, ideally covering the full lifecycle from research through production deployment.

• Previous professional experience in Ad-Tech is required, with relevant exposure to programmatic advertising or mobile advertising technologies.

• Strong programming skills, particularly in Python, with a focus on clean, reproducible, maintainable, and well-tested code.

• Practical experience with technologies such as Spark, Hadoop, Airflow, Docker, and SQL.

• Hands-on experience developing algorithms for sparse and large-scale datasets, including prediction, clustering, and outlier detection.

• Experience building neural-network-based products for classification, regression, multi-task learning, or similar applications is highly valuable.

• Knowledge of reinforcement learning and large-scale optimization problems is an advantage.

• Strong SQL skills and a good understanding of dashboards and monitoring tools.

• Ability to work effectively with large datasets and complex machine-learning systems operating at scale.

• Strong analytical and problem-solving abilities, combined with a pragmatic approach to selecting appropriate solutions.

• Excellent communication and collaboration skills, with the ability to work effectively alongside data scientists, analysts, engineers, and other stakeholders.

• A strong experimentation mindset and willingness to continuously research, test, and refine new approaches.

• Ability to focus on tangible product and business outcomes rather than applying technology for its own sake.

Benefits:

• Direct collaboration with founders and the opportunity to make a visible impact.

• Strong opportunities for career development and continuous learning.

• Opportunity to work alongside experienced data scientists, engineers, entrepreneurs, and industry specialists.

• International and multicultural team distributed across Europe, Asia, North America, and other regions.

• Flexible work-from-home arrangement.

• Opportunity to relocate to an office in Berlin.

• USD $500 home-office setup budget.

• USD $1,000 annual learning and development budget.

• Opportunity to work on machine-learning systems processing massive datasets and real-time advertising workloads.

• Exposure to challenging data science problems across large-scale programmatic advertising and machine learning.