Associate Data Analytics (Credit)

Fortunize Consulting Group; Hyderabad; On-site; INR 600,000 - 1,000,000; Full time

Job summary

Fortunize India Solutions Private Limited in Hyderabad is seeking a Data Analyst to build and optimize dashboards, reports, and data pipelines that support loan origination, underwriting, and portfolio management.

The ideal candidate will have 2–4 years in data analysis or BI, strong SQL skills, and proficiency with Tableau or Power BI; collaboration and precise data governance are essential. Experience with Looker and cloud data environments is a plus; meticulous attention to detail required.

Qualifications

• Bachelor’s degree in a quantitative field.
• 2–4 years of data analysis or BI experience in fintech, financial services, or lending.
• Strong SQL and relational databases experience.
• Proficiency with Tableau or Power BI; Looker is a plus.
• Attention to detail and data accuracy.
• Excellent communication to explain findings to non-technical audiences.

Responsibilities

• Design, build, and maintain dashboards and recurring reports to track KPIs for loan volume, processing times, approval rates, and servicing metrics.
• Collaborate with operations, credit risk, underwriting, product, and finance teams to translate business requirements into data queries and visualizations.
• Ensure data accuracy and integrity across operational reports, proactively identifying and resolving discrepancies.
• Analyze trends in application flow, merchant behavior, and performance to inform process improvements.
• Develop documentation and maintain data dictionaries to support governance and self-service.
• Support ad hoc reporting requests and cross-functional data initiatives.

Skills

SQL

Tableau

Power BI

Looker

Python

R

Data analysis

Education

Bachelor’s degree in a quantitative field

Tools

Snowflake

Redshift

Job description

Fortunize India Solutions Private Limited | Full time

The Data Analyst, will play a key role in enabling data-informed decision-making across our commercial vertical. This position is responsible for developing, maintaining, and optimizing data, reporting tools and dashboards that support loan origination, underwriting, and portfolio management. The ideal candidate is detail-oriented, technically proficient, and highly collaborative.

Requirements

• Design, build, and maintain operational dashboards and recurring reports to track key performance indicators (KPIs) related to loan volume, processing times, approval rates, and servicing metrics.
  
• Collaborate with operations, credit risk, underwriting, product, and finance teams to identify reporting needs and translate business requirements into efficient data queries and visualizations.
  
• Ensure data accuracy and integrity across operational reports, proactively identifying and resolving discrepancies or anomalies.
  
• Analyze trends in application flow, merchant behavior, and advance performance to inform process improvements and resource planning.
  
• Develop documentation and maintain data dictionaries to support data governance and stakeholder self-service.
  
• Support ad hoc reporting requests and contribute to cross-functional data initiatives.
  

Required Experience & Skills:

• Bachelor’s degree in a quantitative field (e.g., Statistics, Business Analytics, Economics, Computer Science, or related discipline).
  
• 2–4 years of experience in data analysis or business intelligence, ideally in fintech, financial services, or lending
  
• Strong SQL skills and experience working with relational databases.
  
• Proficiency with data visualization tools (e.g., Tableau, Power BI, Looker, or similar).
  
• Excellent attention to detail and commitment to data accuracy.
  
• Strong communication skills, with the ability to explain technical findings to non-technical audiences.
  

Qualifications:

• Familiarity with small business lending workflows and key operational metrics.
  
• Experience with Python or R for data manipulation and analysis.
  
• Understanding of data governance, KPI definition, and dashboard usability best practices.
  
• Exposure to cloud-based data environments (e.g., Snowflake, Redshift).