AI Data Analyst

3 - 6 years

5 - 8 Lacs

Posted:None| Platform: Naukri logo

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Job Type

Full Time

Job Description

In this role, you will have the opportunity to:
  • Cross-functional Collaboration: Collaborate with data stewards, OpCo stakeholders, IT professionals, data engineers, and data scientists to assess data requirements, address quality concerns, and achieve consensus on AI use-case specifications.
  • Pipeline & Model Support: Work closely with engineering teams to validate data during pipeline development and model training, ensuring adherence to quality standards and documenting data lineage and rules.
  • Documentation & Enablement: Maintain clear documentation of analytics requirements, data standards, and best practices to support scalable, well-governed data preparation for AI projects
  • Data Quality & Governance: Conduct data profiling, cleansing, validation, and root cause analysis to ensure supply chain master data is accurate, complete, consistent, and time, supporting AI and advanced analytics initiatives.
  • Communication & Remediation: Translate data quality issues into business impact for non-technical stakeholders and recommend remediation strategies or workarounds when needed.
The essential requirements of the job include:
  • Effective collaboration with technical teams and business stakeholders across different operating companies.
  • Strong ability to interpret business goals and analytics requirements, translating them into clear, actionable data quality criteria and plan
  • Proven experience working in data quality, data management, or analytics roles, ideally within supply chain, manufacturing, or a related domain.
  • Demonstrated experience in managing supply chain data domains such as Material Master, Vendor Master, and Customer Master records .
  • Strong understanding of data quality concepts, profiling techniques, and root cause analysis.
It would be a plus if you also possess previous experience in:
  • Understanding of data requirements and data preparation methodologies specifically for Artificial Intelligence and Machine Learning applications or any large-scale data initiatives.
  • Navigating data management complexities within a decentralized or federated organizational structure involving multiple business units or operating companies.

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