Company

FinTech

MarketDataAnalyst

₹22–35L ~AI est. India FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“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.

FinTech
Problems you'll solve

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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