Senior Data Analyst

1. Education & Experience

• Bachelor’s degree in Computer Science, Statistics, Mathematics, Economics, or a related field
  
• Minimum of 5 years’ experience in data analysis or analytics roles
  
• Proven experience working with:
  
• Large and complex datasets
  
• Cross-functional teams (product, finance, operations, technology)
  
• Experience in financial services, fin tech, or lending environments is a strong advantage
  

2. Technical Skills (Non-Negotiable)
Data Handling & Querying

• Advanced SQL,
  
• Experience with relational databases such as PostgreSQL or MySQL
  
• Experience with advanced excel
  

Programming

• Strong proficiency in Python (preferred) or R
  
• Experience with data analysis libraries such as Pandas and NumPy
  
• Familiarity with Scikit-learn or similar tools is an added advantage
  

Data Visualization & BI

• Hands-on experience with Power BI or Tableau
  
• Ability to:
  
• Build and maintain dashboards
  
• Design KPI tracking systems
  
• Present insights in a clear and compelling manner
  

Data Modeling & Warehousing

• Strong understanding of data modeling concepts (e.g., star and snowflake schemas)
  
• Experience with ETL/ELT processes
  
• Familiarity with tools such as dbt, Airflow, or equivalent
  

3. Analytical & Business Skills

• Ability to translate business problems into structured data analyses
  
• Strong experience defining, tracking, and interpreting KPIs
  
• Proficiency in root cause analysis and problem diagnosis
  
• Experience with:
  
• Cohort analysis
  
• Funnel analysis
  
• Forecasting and trend analysis
  
• Understanding of:
  
• A/B testing methodologies
  
• Statistical significance and interpretation
  

4. Problem-Solving & Critical Thinking

• Ability to work with ambiguous or incomplete data
  
• Strong capability in identifying and resolving data quality issues
  
• Structured approach to solving complex and unstructured problems
  
• High attention to detail, particularly in financial or operational contexts
  

5. Communication & Stakeholder Management

• Ability to present insights clearly to non-technical stakeholders
  
• Proven ability to influence decision-making using data
  
• Skilled in simplifying complex analyses into actionable insights
  
• Experience working with:
  
• Senior leadership
  
• Product and operations teams
  

6. Data Governance & Quality

• Experience with:
  
• Data validation and cleaning processes
  
• Data integrity checks
  
• Documentation of data definitions and standards
  
• Ability to:
  
• Establish and maintain data quality frameworks
  
• Ensure consistency and reliability across multiple systems
  

7. Leadership & Ownership

• Ability to own analytics initiatives end-to-end
  
• Experience mentoring junior analysts
  
• Demonstrated ability to promote a data-driven culture
  
• Experience leading:
  
• Reporting automation initiatives
  
• Dashboard standardization efforts
  

8. Nice-to-Have Skills

• Exposure to machine learning concepts and techniques
  
• Experience with APIs and data integrations
  
• Familiarity with cloud platforms such as AWS, GCP, or Azure
  
• Additional exposure to:
  
• Real-time analytics systems
  
• Fraud detection or risk analytics environments