3.0 - 7.0 years

0 Lacs

karnataka

On-site

In this role, you will have the opportunity to collaborate with various stakeholders including data stewards, OpCo stakeholders, IT professionals, data engineers, and data scientists to assess data requirements and address quality concerns. Your main focus will be to achieve consensus on AI use-case specifications through cross-functional collaboration. Additionally, you will work closely with engineering teams to validate data during pipeline development and model training, ensuring adherence to quality standards. It will be your responsibility to document data lineage and rules to support the pipeline and model development process. Maintaining clear documentation of analytics requirements, data standards, and best practices is essential to support scalable and well-governed data preparation for AI projects. You will also be responsible for conducting data profiling, cleansing, validation, and root cause analysis to ensure that supply chain master data is accurate, complete, consistent, and timely. To effectively communicate data quality issues to non-technical stakeholders, you will need to translate them into business impacts and recommend remediation strategies when necessary. The essential requirements for this role include effective collaboration with technical teams and business stakeholders from different operating companies. You should have a strong ability to interpret business goals and analytics requirements, translating them into actionable data quality criteria and plans. Previous experience in data quality, data management, or analytics roles, ideally within the supply chain, manufacturing, or related domains, is preferred. Demonstrated experience in managing supply chain data domains such as Material Master, Vendor Master, and Customer Master records is also valuable. A strong understanding of data quality concepts, profiling techniques, and root cause analysis is required for this role. Having previous experience in understanding data requirements and data preparation methodologies for Artificial Intelligence and Machine Learning applications or large-scale data initiatives would be advantageous. Navigating data management complexities within a decentralized or federated organizational structure involving multiple business units or operating companies is also a desirable skill. Join our team today and be a part of accelerating the real-life impact of tomorrow's science and technology. At Danaher, we value diversity and embrace the unique perspectives contributed by our associates, customers, and shareholders. Visit www.danaher.com for more information.,

Posted 21 hours ago

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