Senior Data Scientist (m/f/d)

Position Summary

Our partner company in Ireland seeks an experienced Senior Data Scientist (m/f/d) to enhance and innovate machine-learning products operating at massive scale within the digital advertising domain. This role involves working extensively with vast, complex datasets and models managing billions of real-time ad requests and user interactions.

Key Responsibilities

• Develop, refine, and sustain machine-learning models embedded in large-scale programmatic advertising systems.
• Boost model performance by integrating new features, optimizing parameters, and leveraging additional data sources.
• Partner with Machine Learning Engineers to research, build, and deploy scalable supervised and unsupervised algorithms.
• Investigate new and existing data sources to uncover opportunities for improving models and overall product efficiency.
• Evaluate and apply machine-learning approaches to optimize different phases of the business and technology chain.
• Design and analyze controlled A/B experiments to verify hypotheses and guide decisions on modeling and product features.
• Create solutions tailored for sparse, high-dimensional datasets focusing on prediction, clustering, and anomaly detection use cases.
• Contribute to neural network-based products for classification, regression, multi-task learning, and related applications.
• Write clean, maintainable, and well-tested code fit for production deployment.
• Develop monitoring frameworks, dashboards, and data-centric tools to track model and system health.
• Collaborate closely with analysts, engineers, and data scientists to translate research insights into practical solutions.
• Maintain a focus on simplicity, experimentation, and measurable impact addressing real business challenges.

Candidate Profile & Requirements

• At least 5 years of professional experience in end-to-end data science or machine learning product development.
• Proven background in Ad-Tech with experience in programmatic or mobile advertising technologies.
• Expert programming skills, especially in Python, emphasizing clean, reproducible, maintainable, and well-tested codebases.
• Hands-on familiarity with Spark, Hadoop, Airflow, Docker, and SQL ecosystems.
• Proven experience designing algorithms for large-scale, sparse datasets involving prediction, clustering, or outlier detection.
• Substantial involvement in neural network-based projects, including classification, regression, and multi-task learning.
• Advantageous knowledge in reinforcement learning and large-scale optimization challenges.
• Strong SQL expertise coupled with experience in monitoring systems and dashboard creation.
• Ability to manage complex machine learning workflows handling substantial datasets at scale.
• Excellent analytical skills combined with practical problem-solving and a result-driven mindset.
• High-level communication and collaboration aptitude working alongside diverse teams.
• An experimental approach, eager for ongoing research, testing, and refining novel methodologies.
• Focus on delivering impactful business and product outcomes beyond mere technical application.

Benefits and Perks

• Direct interaction with company founders, providing visible impact opportunities.
• Strong career growth potential with continual learning paths.
• Work alongside experienced data scientists, engineers, entrepreneurs, and domain experts.
• Join a culturally diverse, international workforce based across Europe, Asia, North America, and more.
• Flexible arrangements allowing some work-from-home flexibility.
• Option to relocate to the Berlin office.
• USD 500 home-office equipment budget allocation.
• Annual USD 1,000 budget for learning and professional development.
• Engage with machine-learning systems processing massive datasets in real-time advertising contexts.
• Experience challenging and meaningful problems in large-scale programmatic advertising and cutting-edge machine learning.

Additional Information

This position is facilitated by a partner organization responsible for managing applications and hiring processes. Applicants will undergo a data-driven selection process supported by artificial intelligence tools to ensure quick, unbiased candidate evaluation. However, final hiring decisions rest with human recruiters. Privacy and data protection compliance are maintained throughout the process.