Data Analyst

Job Description – Data Analyst

Location: Bangalore/Hybrid

About MIC Global

MIC Global is a full-stack micro-insurance provider, purpose-built to design and deliver embedded parametric micro-insurance solutions to platform companies. Our mission is to make insurance more accessible for new, emerging, and underserved risks using our MiIncome loss-of-income products, MiConnect, MiIdentity, Coverpoint technology, and more — backed by innovative underwriting capabilities as a Lloyd's Coverholder and through our in-house reinsurer, MicRe.

We operate across 12+ countries, with our Global Operations Center in Bangalore supporting clients worldwide, including a leading global ride-hailing platform and a top international property rental marketplace. Our distributed teams across the UK, USA, and Asia collaborate to ensure that no one is beyond the reach of financial security.

Role Overview

As a Data Analyst at MIC Global, you will play a key role in transforming data into actionable insights that inform strategic and operational decisions. You will work closely with Product, Engineering, and Business teams to analyze trends, build dashboards, and ensure that data pipelines and reporting structures are accurate, automated, and scalable.

This is a hands-on, analytical, and technically focused role ideal for someone experienced in data analytics and engineering practices. You will use SQL, Python, and modern BI tools to interpret large datasets, support pricing models, and help shape the data-driven culture across MIC Global.

Key Responsibilities

Data Analytics & Insights

• Analyze complex datasets to identify trends, patterns, and insights that support business and product decisions.
• Partner with Product, Operations, and Finance teams to generate actionable intelligence on customer behavior, product performance, and risk modeling.
• Contribute to the development of pricing models, ensuring accuracy and commercial relevance.
• Deliver clear, concise data stories and visualizations that drive executive and operational understanding.
  
  

Data Engineering & Pipeline Management

• Collaborate with Data Engineers to design, implement, and maintain reliable data pipelines and ETL workflows.
• Write clean, efficient scripts in Python for data cleaning, transformation, and automation.
• Ensure data quality, integrity, and accessibility across multiple systems and environments.
• Work with Azure data services to store, process, and manage large datasets efficiently.
  
  

Business Intelligence & Reporting

• Develop, maintain, and optimize dashboards and reports using Power BI (or similar tools).
• Automate data refreshes and streamline reporting processes for cross-functional teams.
• Track and communicate key business metrics, providing proactive recommendations.
  
  

Collaboration & Innovation

• Collaborate with engineers, product managers, and business leads to align analytical outputs with company goals.
  
• Support the adoption of modern data tools and agentic AI frameworks to improve insight generation and automation.
  
• Continuously identify opportunities to enhance data-driven decision-making across the organization.
  
  

Required Qualifications

• 6+ years of relevant experience in data analysis or business intelligence, ideally within product-based SaaS, fintech, or insurance environments.
• Proven expertise in SQL for data querying, manipulation, and optimization.
• Hands-on experience with Python for data analytics, automation, and scripting.
• Strong proficiency in Power BI, Tableau, or equivalent BI tools.
• Experience working in Azure or other cloud-based data ecosystems.
• Solid understanding of data modeling, ETL processes, and data governance.
• Ability to translate business questions into technical analysis and communicate findings effectively.
  
  

Preferred Attributes

• Experience in insurance or fintech data environments, especially pricing and risk analytics.
• Exposure to agentic AI and modern data stack tools (e.g., dbt, Snowflake, Databricks).
• Familiarity with statistical analysis or machine learning techniques for predictive insights.
• Strong attention to detail, analytical curiosity, and business acumen.
• Collaborative mindset with a passion for driving measurable impact through data.
  
  

Benefits

• 33 days of paid holiday
• Competitive compensation well above market average
• Work in a high-growth, high-impact environment with passionate, talented peers
• Clear path for personal growth and leadership development
  
  

Role reports into:

Head of Technology

Shivaprashanth Nuji | LinkedIn

COO

Harry Croydon I LinkedIn