Senior Data Scientist (f/m/d)

Established in 2000, Awin is part of the Axel Springer group. Awin focuses on building the world’s leading open partner ecosystem and supports a diverse and inclusive culture.

• 5+ years of experience as a Data Scientist, Machine Learning Engineer, Applied Scientist, or similar role.
• Proven experience delivering machine learning and analytical solutions from discovery through deployment and business impact.
• Advanced proficiency in Python and relevant data science libraries, including NumPy, PySpark, Scikit-learn, TensorFlow, and/or PyTorch.
• Strong experience using Databricks, including Jobs, Asset Bundles, Delta Lake, and MLflow.
• Experience collaborating with business stakeholders to define problems, scope solutions, and communicate outcomes.
• Experience mentoring data scientists or providing technical leadership within a cross-functional team.
• Bachelor's degree or higher in Statistics, Mathematics, Computer Science, Data Science, Engineering, or related quantitative discipline.
• Strong statistical, analytical, and problem-solving skills.
• Expertise in machine learning and predictive modelling with deployment experience.
• Ability to evaluate and refine models using experimentation and performance metrics.
• Strong stakeholder management and communication skills.
• Ability to operate independently and prioritize tasks for business impact.
• Collaborative mindset for effective cross-team work.

• Lead development and deployment of machine learning, forecasting, recommendation, and analytical solutions creating measurable business impact.
• Partner with Product, Commercial, Engineering, and Data teams to identify opportunities and translate business challenges into data-driven solutions.
• Design and implement evaluation frameworks, experiments, and success metrics to measure performance and business outcomes.
• Apply statistical modelling, machine learning, and advanced analytical techniques to solve complex business problems.
• Build scalable feature engineering, model development, and deployment workflows with Data Engineering and Software Engineering teams.
• Drive rapid MVP development ensuring sustainable production solutions.
• Define and promote best practices for model development, evaluation, monitoring, and governance.
• Mentor and support other data scientists, contributing to technical capability and knowledge sharing.
• Communicate findings, recommendations, and technical concepts clearly to technical and non-technical audiences.
• Contribute to the evolution of the Data Science roadmap, identifying new opportunities for advanced analytics and machine learning.