We are looking for an experienced Senior Data Scientist (MDM) to join global projects in master-data intelligence. In this role, you will own the end-to-end development of ML models that reconstruct business rules from SAP and non-SAP data and drive best practices that ensure our adaptive rule engines scale with the business.
Key Responsibilities
Architect, build, and optimize Py Spark-based ML pipelines that infer hidden business logic from millions of legacy records
Lead technical design reviews and establish MLOps standards for adaptive rule-discovery systems
Collaborate with data engineers, SAP functional leads, and business analysts to translate undocumented behaviors into validated, high-confidence business rules
Diagnose and resolve performance bottlenecks, data-drift issues, and cross-platform inconsistencies in real-time inference jobs
Mentor junior and mid-level engineers through pair programming, code reviews, and knowledge-sharing sessions on large-scale feature engineering
Own release planning, CI/CD pipelines, and automated testing strategies to maintain >95 % model-accuracy benchmarks
Need to Haves
5+ years of production experience with Py Spark, Databricks, and Azure cloud services
Proven track record of delivering scalable, high-performance ML solutions for pattern recognition and rule inference
Strong English skills—comfortable presenting model decisions to stakeholders and writing detailed RFCs
Demonstrated leadership in driving data-science excellence and mentoring teams
Nice to Haves
Deep domain expertise in master-data management (golden records, lineage, MDM quality frameworks)
Experience building and governing enterprise-grade ML feature stores or adaptive rule libraries
Proficiency with SAP MDG and understanding of SAP master-data structures