Senior Data Scientist

About the Role

A partner company is seeking a Senior Data Scientist based in Ireland to develop and enhance machine learning solutions at a large global scale. The role involves handling vast, intricate datasets and machine learning models that process billions of ad requests and users in real-time. This position covers the entire data science lifecycle from research to deployment and ongoing optimization.

Working closely with data scientists, analysts, and machine learning engineers, you will create scalable solutions that deliver clear business outcomes, improving advertising effectiveness globally, including customer acquisition and retargeting efficiencies.

You will have considerable freedom to experiment with new algorithms, data integrations, and modeling techniques. Joining a distributed international team, you will contribute to a dynamic environment committed to innovation, collaboration, and continual learning.

Key Responsibilities

• Design, develop, and refine machine learning models by adding new features, tuning parameters, and integrating extra data sources.
• Partner with machine learning engineers to research, develop, and deploy both supervised and unsupervised scalable learning algorithms.
• Investigate new and existing data sources to find opportunities to enhance model accuracy and devise data-driven solutions.
• Research and assess innovative machine learning methods to optimize various stages of product and advertising value chains.
• Plan and analyze A/B experiments to test hypotheses, assess impact, and incrementally improve models and strategies.
• Create solutions that handle sparse and voluminous datasets for prediction, clustering, and anomaly detection tasks.
• Contribute to neural network-based projects involving classification, regression, and multi-task learning.
• Write clean, maintainable, reproducible, and well-tested code suitable for transitioning from research to production environments.
• Develop and enhance monitoring dashboards and tools to track performance of models and systems.
• Collaborate effectively with analysts, engineers, and fellow data scientists to translate business challenges into machine learning solutions.
• Adopt an experimentation-first approach focusing on impactful, straightforward solutions rather than unnecessary complexity.

Qualifications and Experience

• Minimum of 5 years’ experience in data science or machine learning product development from research stages to production deployment.
• Strong programming capabilities with dedication to writing clean, maintainable, and well-tested code.
• Proficient hands-on experience with Python, Spark, Hadoop, Airflow, Docker, and SQL.
• Demonstrated expertise with algorithms suited for sparse and large-scale datasets, including prediction, clustering, and outlier detection.
• Valuable practical experience developing neural network solutions for classification, regression, or multi-task learning.
• Knowledge of reinforcement learning and large-scale optimization techniques is a significant plus.
• Solid understanding of SQL and dashboard tools to monitor and enhance data science and machine learning workflows.
• Strong communication and teamwork skills to cooperate with various data teams.
• A pragmatic, experimental mindset focused on measurable business results through machine learning interventions.
• Required prior professional experience in AdTech, ideally with mobile app advertising technology exposure.

Benefits

• Direct engagement with company founders, influencing product and business strategies.
• Robust opportunities for career advancement, learning, and skill development.
• Work alongside seasoned industry professionals and entrepreneurs within a rapidly evolving tech sector.
• Be part of a diverse and multinational distributed team across Europe, North America, Asia, and beyond.
• Flexible arrangements allowing work-from-home.
• Potential to relocate to an international office in Berlin.
• Home office setup allowance of $500.
• Annual budget of $1,000 dedicated to learning and professional development.

Additional Information

This role is managed by a partner company that handles all applications and subsequent recruitment procedures. The application review process uses AI-powered matching to swiftly identify top candidates who are then forwarded to the employer for final selection. All final interview and assessment decisions lie with the hiring company.

Applicants are reminded that submitting an application authorizes the processing of personal information in compliance with data privacy laws, including GDPR. AI tools may assist in reviewing applications, but hiring decisions remain human-led.