Reporting Analyst
mea
Job Description
Reporting Analyst
Role Overview
The Reporting Analyst is responsible for measuring, analysing, and communicating the business value that Mea Platform delivers to our insurance clients. This role transforms raw platform usage data, client operational metrics and Mea operational support data into compelling stories of ROI, efficiency gains, and process improvements that drive renewals, expansions, customer advocacy and operational efficiency for Mea.
Why This Role Exists Now
Scale Challenge: With a rapidly growing client list, we need systematic measurement of client success
ROI Validation: Fact based proof of value to justify renewals and expand usage
Product Insights: Usage data reveals what's working (and what's not) to guide roadmap
Sales Enablement: Quantified results from existing clients drive new business
Operational Excellence: Data-driven insights help improve support and implementation methodologies
Core Responsibilities
1. Client Value Measurement
What:
Design and implement measurement frameworks for each client to track mea's impact
Define KPIs by process: submission intake, underwriting, claims, bordereaux processing
Establish baseline metrics (pre-mea state) and track ongoing performance
Calculate ROI metrics: time savings, cost reduction, capacity improvement, revenue impact
Create client-specific dashboards showing real-time value delivery
Deliverables:
Client Value Scorecards (monthly per client) ο· ROI Calculation Models (custom per client) Executive-ready dashboards (Tableau, PowerBI, or similar)
Quarterly Business Review (QBR) data packages
Annual value realization reports
Success Metrics:
100% of clients have active value measurement frameworks
QBRs include quantified ROI data (not just usage stats)
Client stakeholders can articulate Mea's value in financial terms
Renewal conversations lead with "here's what we delivered" data
2. Data Analysis & Insights (30%)
What:
Analyze platform usage data to identify patterns, trends, and anomalies
Investigate drops in usage or adoption issues
Identify opportunities for clients to expand usage to new workflows
Benchmark performance across clients (anonymized)
Conduct root cause analysis when expected value isn't being realized
Translate technical metrics into business impact
Work with QA team to drive accuracy reporting for clients
Deliverables:
Monthly Usage & Adoption Reports (internal)
Client Health Scorecards (red/yellow/green flags)
Expansion Opportunity Analysis (which clients should get which new features)
Benchmark Reports (how Client A compares to similar implementations)
Ad-hoc analysis requests from Customer Success and Product teams
3. Reporting & Communication
What:
Create executive-ready presentations for client QBRs
Develop case studies with quantified results
Produce internal reports for leadership (customer health, product usage, trends)
Build reusable templates for consistent reporting
Communicate findings to both technical and non-technical audiences
Support sales team with proof points and ROI models
Deliverables:
Quarterly Business Review decks (per client)
Case studies for marketing and sales use
Monthly leadership dashboard (portfolio health)
Client success stories with specific metrics
Sales enablement materials (ROI calculators, comparison charts)
4. Process Improvements & Automation
What:
Automate repetitive reporting tasks
Build self-service dashboards for internal teams
Improve data collection processes with clients
Standardize metrics definitions across clients
Optimize reporting infrastructure and tools
Document best practices for value measurement
Deliverables:
Automated monthly reporting workflows
Self-service analytics portal for CSMs and Account Managers
Standardized metrics dictionary
Data collection process documentation
Reporting SLA and quality standards
Required Qualifications
Insurance Industry Knowledge (Critical)
Must Have:
3-5 years working in a similar role in insurance operations, analytics, or reporting
Deep understanding of insurance workflows: underwriting, claims, finance/accounting
Familiarity with insurance systems (Guidewire, Duck Creek, applied systems, etc.)
Knowledge of insurance KPIs and operational metrics
Understanding of insurance business model and value drivers
Nice to Have:
Experience at multiple carriers (see different operating models)
Exposure to insurance consulting or systems implementations
Background in process improvement or operational excellence
Familiarity with reinsurance operations
Technical Skills (Critical)
Must Have:
Advanced Excel/Google Sheets (pivot tables, complex formulas, data modeling)
SQL for querying databases
Data visualization tools (Tableau, PowerBI, Looker, or similar)
Statistical analysis fundamentals
Understanding of APIs and data integration concepts
Nice to Have:
Python or R for advanced analytics
Experience with BI platforms (Snowflake, BigQuery, etc.)
ETL/data pipeline knowledge
Basic scripting for automation
Analytical Skills (Critical)
Must Have:
Strong quantitative and analytical thinking
Ability to identify patterns and trends in data
Root cause analysis and problem-solving
Translate data into actionable insights
ROI and financial modeling capabilities
Statistical literacy (averages, distributions, correlations, etc.)
Communication Skills (Critical)
Must Have:
Excellent presentation skills
Data storytelling ability (not just showing charts, but explaining "so what?")
Written communication (clear, concise reports and documentation)
Ability to explain technical concepts to non-technical audiences
Comfortable presenting to C-level executives
Personal Attributes
Must Have:
Detail-oriented and quality-focused
Self-starter who doesn't need constant direction
Intellectual curiosity about why data looks the way it does
Customer-centric mindset ο· Collaborative team player
Comfortable with ambiguity and building processes from scratch
Nice to Have:
Experience in startup or high-growth environment
Comfort with rapid change and iteration
Entrepreneurial mindset
Location Bangalore, India