Data Steward – Quality Excellence

Job not on LinkedIn

🔥 0 minutes ago

🇮🇳 India – Remote

⏰ Full Time

🟠 Senior

🔴 Lead

✨ Data Steward

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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AlphaSense

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2011

💼 Consulting

🏥 Healthcare

📣 Marketing

💰 Debt Financing on 2022-06

Consulting • Healthcare • Marketing

AlphaSense is a market intelligence and search platform that empowers companies to unlock critical insights across an extensive universe of public and private content, including company filings, broker research, expert calls, and market trends. Its AI-driven technology affords users the ability to conduct comprehensive due diligence with speed and accuracy, reducing uncertainty and blind spots in decision-making. Trusted by major corporations, financial institutions, and asset management firms globally, AlphaSense serves sectors such as financial services, health care, and technology by providing generative AI-powered solutions that integrate internal proprietary data with external premium content.

📋 Description

• Establish and maintain data quality standards, business rules, metadata definitions, and taxonomy frameworks across content domains • Monitor dataset health and quality metrics to improve accuracy, completeness, consistency, and timeliness • Investigate recurring data-quality issues and conduct root cause analysis • 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 • 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 • Establish a unified quality framework and consistent metadata and taxonomy standards • Build quality dashboards providing visibility into dataset health • Drive recurring quality issues to root-cause resolution • Pilot at least one AI or automation opportunity with measurable efficiency gains

🎯 Requirements

• 8+ years of experience in data governance, data quality, content operations, product operations, information management, or a related field • Demonstrated experience with root cause analysis and cross-functional process improvement • Experience working with structured and unstructured datasets • Experience in financial information services or related industries preferred • Strong analytical and problem-solving skills • Ability to navigate ambiguity and manage multiple priorities • Excellent collaboration and communication skills • Experience working across Operations, Product, Engineering, and Quality teams • Experience defining operational metrics, standards, processes, and documentation • Lean Six Sigma Green Belt certification preferred • Familiarity with SQL, BI tools, AI workflows, or metadata management preferred

🏖️ Benefits

• Equal-opportunity employer committed to a supportive, respectful work environment • Reasonable accommodation for qualified employees with protected disabilities, as required by applicable laws • Opportunity for broad cross-functional exposure and influence over data quality and governance practices