Data Analyst
- SQL
- Python
- Data quality
- Statistics
Analytics portfolio
Lochanreddy Mallakunta
Turning data into decisions across BI, business, operations, marketing, and product.
SQL, Python, Power BI, and Tableau — turned into decisions stakeholders can act on.
Role map
One analytical foundation
Data → Insight → Decision. Titles change. The craft stays consistent.
FOUNDATION
Data → Insight → Decision
BI / Reporting Analyst
- Power BI
- Excel
- DAX
- KPI reporting
Business Analyst
- Requirements
- Process analysis
- Recommendations
- Stakeholder communication
Operations Analyst
- Process metrics
- Forecasting
- SLA analysis
- Optimization
Marketing Analyst
- Campaign measurement
- Segmentation
- Attribution
- Experimentation
Product Analyst
- Funnels
- Retention
- Behavioral analysis
- Product KPIs
Featured work
Case studies for a 60-second scan
Each study leads with the problem and outcome. Evidence lives on the detail pages.
FeaturedFintech
DigiPae Payment and Product Analytics
Problem: Where do users and merchants encounter friction across signup, identity verification, bank linking, payment initiation, and successful completion—and which issues should be prioritized?
Outcome: A measurement framework for identifying friction across onboarding, verification, bank linking, and payment completion.
Tools: SQL · Excel · Power BI · Python
FeaturedSmart City
Smart-City Research Analytics
Problem: Where is traffic and PM2.5 pressure concentrated across monitored junctions, how do conditions change over time, and which early-warning signals should operators review first?
Outcome: Led data systems and BI reporting for an urban analytics prototype monitoring real-time traffic and PM2.5 across 5+ city junctions.
Tools: Python · SQL · Excel · Power BI
FeaturedTax / Finance
H&R Block Tax Analytics & Automation
Problem: Where do filing workflows bottleneck, which error patterns need attention, and how can ETL and reporting automation improve processing efficiency and leadership visibility?
Outcome: Analyzed filing patterns and bottlenecks, restructured ETL pipelines for about 40% faster processing, and delivered Power BI dashboards with automated validation.
Tools: Excel · Power BI · SQL · Power Query · Python · DAX
FeaturedHealthcare
AI-Driven Healthcare Analysis & Reporting
Problem: Which health-metric patterns should receive additional review, how can anomaly detection reduce time-to-insight, and what access controls are required for trustworthy monitoring?
Outcome: Built an AI-powered anomaly detection and reporting workflow for critical health-metric patterns, paired with role-based BI dashboards for faster monitoring.
Tools: Python · SQL · Excel · Machine Learning
Skills grouped by how the work gets done
Data querying and preparation
- SQL
- Excel
- Power Query
- Python
- Relational databases
- Data validation
- Data cleaning
Business intelligence
- Power BI
- DAX
- Tableau
- Dashboard design
- KPI development
- Reporting automation
- Advanced Excel
Analysis
- Exploratory analysis
- Trend analysis
- Segmentation
- Cohort analysis
- Funnel analysis
- Forecasting
- Anomaly detection
- Model evaluation
Business and operations
- Requirements analysis
- Process mapping
- Root-cause analysis
- Operational metrics
- Stakeholder communication
- Decision support
Product and marketing
- Activation
- Retention
- Conversion funnels
- Campaign performance
- Customer segmentation
- Attribution concepts
Founder perspective
Founder perspective, analyst discipline
Building DigiPae at CEIVIS is applied analytics and business ownership—not a startup pitch, and not unverified traction.
Founder & Full-Stack Developer · DigiPae (Ceivis LLC)
- Measurable product questions
- Payment and identity workflows
- User and merchant funnels
- KPI and compliance reporting
Experience and education
Experience
Founder & Full-Stack Developer
DigiPae (Ceivis LLC) · Oct 2025 – Present · St. Louis, MO
Building DigiPae, a payments and verified-identity platform. Instrumented product analytics with Mixpanel for payment funnels, onboarding drop-off, KYC conversion, and retention; designed KPI dashboards for transaction volumes, error rates, and compliance metrics; reconciled multi-vendor data flows (Stripe, Socure, Plaid, Firebase) into consistent reporting views.
Data & BI Lead
Smart-City Research Project · Saint Louis University · Aug – Dec 2025 · St. Louis, MO
Led backend data systems and BI reporting for an urban analytics prototype monitoring real-time traffic and PM2.5 air quality across 5+ city junctions. Built Python ETL pipelines with forecasting models and a responsive BI dashboard with live telemetry, scenario testing, and early-warning signals.
Data Analyst Intern
Gateway Region YMCA · May – Oct 2024 · St. Louis, MO
Wrote complex SQL against SQL Server for membership, program, and financial reporting. Built Power BI dashboards and Excel reports with validation checks. Automated recurring extraction and reporting with Python (Pandas), reducing manual reporting effort by approximately 35% per resume.
Cloud Developer
TVM Infotech Private Limited · Oct 2023 – Dec 2024 · Chennai, India
Developed and optimized SQL against PostgreSQL and MySQL; built Python ETL across AWS (S3, RDS, Lambda, EC2); wrote stored procedures and cursors for recurring reporting workflows, reducing manual data preparation time by approximately 30% per resume.
Education
Master of Science — Information Systems
Saint Louis University · St. Louis, MO
Graduate study in Information Systems, including master’s research work on smart-city analytics.
Bachelor of Technology — Computer Science & Engineering
Sree Vidyanikethan Engineering College · Undergraduate degree
Computer Science & Engineering foundation supporting data systems, cloud, and analytics work.
Analytical approach
01
Frame the business question
Translate a decision need into a measurable question with clear success criteria.
02
Validate and prepare the data
Assess coverage, quality, and definitions before drawing conclusions.
03
Analyze patterns and causes
Compare segments, trends, and exceptions to isolate what drives outcomes.
04
Communicate findings visually
Present the few charts and tables that help stakeholders decide quickly.
05
Recommend and measure action
Propose next steps with owners, expected signals, and follow-up metrics.
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