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Data Operations

Azeus Convene · Noida, Uttar Pradesh, India

Operations ManagementEntry LevelQuick applycontract17 days ago

About The Role

We are seeking a Data Operations Associate to support our data quality and operational excellence, ensuring our data platform maintains the highest standard of buyer insights and deal information.

● Work at the intersection of data, finance, and technology.

● Contribute directly to the accuracy and quality of a product that powers deal-making for thousands of firms.

● Be part of a collaborative, high-growth environment with opportunities to expand your skills in data operations and marketplace research.

Responsibilities

In this role, you will be responsible for

  1. Data and Content Management
  • ○ Ingest, curate, and validate structured and unstructured data.
  • ○ Conduct research to verify, normalize, and enrich company and deal-related information.
  • ○ Update, maintain, and improve inaccurate records in both the internal database and client-facing content.
  1. Data Quality & Standards
  • ○ Implement best practices in data management, usability, and quality control.
  • ○ Uphold accuracy and consistency standards across product deliverables and the proprietary Axial member database.
  1. Cross-Team Collaboration
  • ○ Communicate progress, challenges, and feedback clearly to domestic counterparts.
  • ○ Advocate for user-centric design in dashboards, APIs, and other data delivery mechanisms.
  1. Operational Support
  • ○ Assist with ad-hoc business operations projects such as company profile enrichment, lead/contract qualification, and deal-sourcing initiatives.
  • ○ Provide support in data-related research and content verification projects.
  • ● Bachelor’s degree required.
  • ● 2+ years of professional experience in data operations, including ingestion, validation, research, and quality assurance.
  • ● Detail-oriented with excellent analytical, problem-solving, and decision-making skills.
  • ● Inquisitive mindset with the ability to interpret information from multiple sources.

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