Data Steward - Quality Excellence in भारत

About AlphaSense: The world’s most sophisticated companies rely on AlphaSense to remove uncertainty from decision-making. With market intelligence and search built on proven AI, AlphaSense delivers insights that matter from content you can trust. Our universe of public and private content includes equity research, company filings, event transcripts, expert calls, news, trade journals, and clients’ own research content. The acquisition of Tegus by AlphaSense in 2024 advances our shared mission to empower professionals to make smarter decisions through AI-driven market intelligence. Together, AlphaSense and Tegus will accelerate growth, innovation, and content expansion, with complementary product and content capabilities that enable users to unearth even more comprehensive insights from thousands of content sets. Our platform is trusted by over 6,000 enterprise customers, including a majority of the S&P 500. Founded in 2011, AlphaSense is headquartered in New York City with more than 2,000 employees across the globe and offices in the U. S. , U. K. , Finland, India, Singapore, Canada, and Ireland. Come join us! About the Role We are looking for an experienced Data Steward / Senior Data Steward – Quality Excellence to help drive data quality, governance, and operational excellence across our diverse content domains. In this role, you will work horizontally across multiple content areas to establish consistent data quality standards, strengthen governance practices, identify systemic issues, and drive scalable improvements. You will partner closely with Content Operations, Product, Engineering, and Quality teams to ensure our datasets are accurate, complete, consistent, scalable, and fit for customer and AI use cases. This is a highly cross-functional role for someone who enjoys solving complex data-quality problems, bringing structure to ambiguity, and turning insights into sustainable improvements. What You'll Do - Establish and maintain data quality standards, business rules, metadata definitions, and taxonomy frameworks across content domains.

- Monitor dataset health and quality metrics to identify opportunities to improve accuracy, completeness, consistency, and timeliness. - Investigate recurring data-quality issues and conduct root cause analysis to develop preventive and scalable solutions. - Partner with operational teams to identify systemic issues and implement process improvements. - Develop and maintain quality dashboards, data dictionaries, governance documentation, and standard operating procedures. - Collaborate with product managers to translate operational insights into product requirements and enhancement opportunities. - Partner with engineering teams to define data-quality requirements and support automation initiatives. - Support complex customer escalations and investigations requiring strong domain and data expertise. - Drive cross-functional initiatives focused on content quality, operational efficiency, and scalability. - Promote standardization and best practices across content domains and workflows. - Identify opportunities to leverage AI and automation to improve quality and reduce manual effort. - Serve as a subject matter expert and trusted partner for data quality and governance initiatives. What Success Looks Like In your first 12 months, you will help: - Establish a unified quality framework across content domains. - Implement consistent metadata and taxonomy standards. - Build quality dashboards that provide meaningful visibility into dataset health and quality. - Drive recurring quality issues to root-cause resolution across multiple domains. - Identify and pilot at least one AI or automation opportunity that delivers measurable efficiency gains. - Establish scalable standards and practices that improve both data quality and operational efficiency.