Company
FinTech
MarketDataAnalyst
Neural analysis suggests this role is
optimal for Senior candidates.
“Market Data Analyst. Skills: Market data analysis, Data quality assurance, Financial data investigation. Design quality assurance methodologies. Implement quality assurance methodologies”
What You'll Achieve.
Ensure highest levels of accuracy; Ensure highest levels of integrity; Improve platform reliability; Improve user experience; Enhance overall quality; Enhance breadth of market intelligence
Industry & Context.
Problem-solving; Investigate data inquiries; Resolve data issues
What They're Looking For.
Must Have
5-7 years experience financial services, Equities data exposure, Market data exposure, Fundamentals exposure, Estimates exposure, Design quality assurance processes, Implement quality assurance processes, Manage quality assurance processes, Understanding of corporate actions, Experience with financial data providers, Familiarity with data feeds, Familiarity with APIs, Familiarity with data integration, Working knowledge of SQL, Communication skills, Fluency in English
Nice to Have
Python scripting experience, Data transformation experience, Quantitative finance concepts knowledge, Financial modeling knowledge, Systematic investment methodologies knowledge, Experience with JIRA
What You'll Do.
Design quality assurance methodologies
Implement quality assurance methodologies
Improve quality assurance methodologies
Conduct quality checks
Identify inconsistencies
Investigate data inquiries
Support data inquiries
Build data validation workflows
Maintain data validation workflows
Optimize data validation workflows
Analyze corporate actions
Ensure accurate representation
Drive data-focused projects
Ensure timely execution
Explore data opportunities
Explore vendor integrations
Explore process improvements
Enhance market intelligence
Document data quality initiatives
Monitor data quality initiatives
Manage data quality initiatives
Document operational improvements
Monitor operational improvements
Manage operational improvements
How You'll Work.
Team & Collaboration
Collaborate with product management; Collaborate with engineering teams; Global team collaboration
Communication Scope
English fluency
Process & Methodology
Project management, Issue-tracking
Full Job Description
## Accountabilities Design, implement, and continuously improve quality assurance methodologies for financial and market data to ensure the highest levels of accuracy and integrity Conduct systematic quality checks across multiple data sources and vendors, identifying inconsistencies and resolving complex data issues Investigate and support escalated financial data inquiries involving stock performance, historical fundamentals, earnings, corporate actions, financial ratios, and market metrics Build, maintain, and optimize data validation workflows and processes that support scalable and reliable data operations Collaborate closely with product management and engineering teams to prioritize, track, and resolve data-related issues through structured project workflows Analyze corporate actions such as dividends, stock splits, earnings events, and other market activities to ensure accurate representation across datasets Drive data-focused projects independently, ensuring timely execution and delivery of solutions that improve platform reliability and user experience Explore new data opportunities, vendor integrations, and process improvements to enhance the overall quality and breadth of market intelligence offerings Utilize tools and systems to document, monitor, and manage ongoing data quality initiatives and operational improvements Requirements: 5–7 years of experience in the financial services industry with strong exposure to equities data, market data, fundamentals, estimates, or related datasets Proven experience designing, implementing, and managing quality assurance processes for financial data environments Strong understanding of corporate actions, including dividends, stock splits, earnings events, and their impact on financial datasets Experience working with leading financial data providers such as Bloomberg, FactSet, S&P Global, or similar platforms Familiarity with data feeds, APIs, and data integration processes within financial systems Working knowledge
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