Dealstitch AI logo
Dealstitch AI
Posted 72 days agoVerified live 11h ago

Data Analyst II

Brief overview

Remote
2+ yrsMinimum
SQLSpreadsheetPythonpandasPower BITableauPrivate-markets dataFinancial data

About the company

Dealstitch AI logo
Dealstitch AIdealstitch.ai

Only 8% of private market investors have successfully deployed AI — and Gartner finds roughly half of all pilots fail before go-live.

Job description

Summary

Dealstitch AI is seeking a Data Analyst II to enhance their engagements through detailed data work. The role involves mapping, reconciling, and validating data across systems, as well as building datasets for performance measurement.

Responsibilities

  • Map, normalize, reconcile, and validate data from source systems into the target schema, partnering with our data team in Hyderabad, India to deliver at scale
  • Profile and clean messy, real-world data from documents, spreadsheets, and exports, and surface the quality issues that matter
  • Build and maintain the ground-truth datasets we measure our agents against, and review agent and extraction outputs for accuracy
  • Turn the results into clear analysis and reporting the team and the client can act on

Skills

  • 2+ years in a data analyst role, with strong SQL and spreadsheet skills
  • A sharp eye for data quality: you catch the nulls, mismatches, and logical errors others miss
  • Comfort working with messy data from many sources and getting it into a clean, structured shape
  • Clear communication: you can turn data findings into something a non-technical stakeholder understands
  • Bonus: Python or pandas, a BI tool such as Power BI or Tableau, or familiarity with private-markets or financial data

Qualifications

Must Haves

  • 2+ years in a data analyst role, with strong SQL and spreadsheet skills
  • A sharp eye for data quality: you catch the nulls, mismatches, and logical errors others miss
  • Comfort working with messy data from many sources and getting it into a clean, structured shape
  • Clear communication: you can turn data findings into something a non-technical stakeholder understands

Nice to Haves

  • Bonus: Python or pandas, a BI tool such as Power BI or Tableau, or familiarity with private-markets or financial data

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