Data Analyst

Experience:

Location:

About the Role

Data Analyst

Key Responsibilities

• Work on

  data science and analytics projects

  , including data cleaning, modelling, and visualization.
• Manage, organize, and analyze

  large financial datasets

  from internal and external sources.
• Build and maintain

  Python-based tools, scripts, and automation workflows

  for data processing.
• Write optimized

  SQL queries

  to extract, process, and analyze data from databases.
• Support

  company evaluation

  , including financial analysis, metric benchmarking, and sector research.
• Assist in evaluating

  debt financing proposals

  , borrower profiling, and repayment capacity assessments.
• Work on

  structured finance

  , asset-backed securities (ABS), or credit analysis of corporate borrowers.
• Prepare dashboards, MIS reports, and insights to support investment and credit decisions.
• Collaborate with investment, credit, and operations teams to improve data frameworks and decision-making tools.

Required Skills & Qualifications

• 2–4 years

  of experience in a finance, fintech, investment, or private credit environment.
• Strong proficiency in

  Python

  (Pandas, NumPy, visualization libraries preferred).
• Strong command over

  SQL

  and relational databases.
• Experience working with

  large datasets

  and data science workflows.
• Exposure to

  company evaluation, ratio analysis, financial modelling

  , or credit assessment.
• Understanding of

  debt financing

  , loan structuring, credit appraisal, or underwriting.
• Familiarity with

  structured finance, asset-backed securities

  , or corporate credit analysis is a strong plus.
• Excellent analytical, problem-solving, and communication skills.

Preferred Qualifications

• Bachelor’s/Master’s in Finance, Engineering, Data Science, Economics, or related field.
• Experience in

  AIF, Private Credit, NBFC, Fintech Lending

  , or Investment Research firms.