Senior Manager Data Science & AI EM

**Job Description:** **Role Overview:** As a Senior Manager Data Science & AI at Adidas, you will be an integral part of the Emerging Markets Data & Analytics (DNA) team. You will lead the Data Science & AI pillar, focusing on driving innovation, experimentation, and ideation to deliver advanced analytics solutions across EM functions and clusters. Your role will be crucial in enabling data-driven decision-making, unlocking new opportunities, and fostering business growth through advanced analytics capabilities like machine learning, generative AI, and agentic systems. You will be responsible for owning the end-to-end lifecycle of advanced analytics solutions, from scoping and development to deployment and operationalization, ensuring alignment with business priorities and global standards. Additionally, you will collaborate with global teams and local functions to ensure technical excellence and cross-functional enablement. **Key Responsibilities:** - Drive the design, development, and deployment of advanced analytics models such as forecasting, classification, clustering, and recommendation systems. - Translate business problems into data science use cases and actionable solutions in collaboration with the BI Analytics DNA pillar. - Support experimentation and implementation of GenAI, agentic AI, and LLMS-based solutions tailored to EM business needs. - Ensure model performance, interpretability, and business relevance. - Co-own the ML Ops lifecycle with the Data Engineering pillar, including model versioning, CI/CD pipelines, monitoring, retraining, and governance. - Collaborate with Data Engineering to ensure scalable data pipelines and integration with Lakehouse (Databricks). - Partner with EM business functions to scope and prioritize high-impact use cases. - Stay updated on emerging trends in AI, ML, GenAI, and agentic systems. - Promote a culture of innovation, agile piloting, and continuous learning within the DNA team. **Qualification Required:** - University degree in Data Science, Computer Science, Mathematics, Engineering, or related field. - 7+ years of experience in data science, machine learning, and AI. - Strong proficiency in Python, SQL, and ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch). - Experience with ML Ops tools (e.g., MLflow, Airflow, Databricks) and cloud platforms (Azure, AWS, GCP). - Excellent communication and stakeholder management skills. - Passion for innovation and continuous improvement. Note: The additional details of the company or any specific values were not explicitly mentioned in the job description provided.,