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Senior Reporting Analyst

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Senior Reporting Analyst

Numerator

Senior Reporting Analyst

Skills

SQL QueriesBig DataData ScienceRMarket ResearchPower BI

13 days ago

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Important information


Contract type:

Permanent

Location:

Vadodara, Gujarat, India

Work mode:

Remote

Published on:

8 October 2026

What they need


We’re reinventing the market research industry. Let’s reinvent it together. At Numerator, we believe tomorrow’s success starts with today’s market intelligence. We empower the world’s leading brands and retailers with unmatched insights into consumer behavior and the influencers that drive it.

We need a Market Research Data Processing Specialist to clean, organize, and analyse survey data. We will use Crunch to turn raw survey responses into clean data assets for our research team.

Key Responsibilities

  • Data Cleaning/ Quality: Check survey data for errors, missing values, and wrong answers.
  • Data Processing: Perform cleaning, data merging, and formatting using available tools/ techniques i.e. R/ Crunch Automation scrips. Etc as per tab speck and questionnaire.
  • Crunch Platform Management: Upload, organize, and maintain datasets within Crunch for team access.
  • Coding Open-Ends: Group and label text answers from open-ended survey questions.
  • Dashboard Support: Help build interactive visual tools and reports for clients within crunch.

What You'll Bring to Numerator Requirements

  • Experience: 4+ years of working experience in market research domain under data processing team.
  • Software Skills: R programing or SPSS or IBM SPSS Dimensions - DMS Validation, Advanced Excel (e.g. Advanced Formulas; Pivot Tables; Macros) is recommended).
  • Attention to Detail: Strong focus on finding and fixing errors in large data sets.
  • Education: A bachelor's degree in Statistics, Math, Data Science, or a related field.

Preferred Skills (Nice-to-Have - Not Mandatory)

  • Software Skills: Power BI/ SQL/ HTML/ Understanding JSON survey schema
  • Data Wrangling: Ability to manipulate data using R libraries (like tidyverse or dplyr).

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