Saikiran G
Full Stack Developer |Java 17| Angular | React JS | Spring Boot | Generative AI | Micro-Services | API Development | AWS | SQL | Rest | Spring | Spring MVC | JavaScript |TypeScript | SQL | CSS
- Role
- Data Analyst at Anthem, Inc
- Location
- Roanoke, TX, US
- LinkedIn followers
- 500 followers
About Saikiran G
I’m Sai Kiran, a Java Full Stack Developer with 6+ years taking ideas from whiteboard to production:• Java 8-17, Spring Boot, WebFlux → fast, non-blocking services• Angular, React, TypeScript → clean, accessible UIs • AWS, Docker, Kubernetes → scale on demand• Kafka, JMS → smooth event flows• PostgreSQL, MongoDB → data that behaves under loadKey wins1⃣ Modernised Stony Brook’s academic & health modules; 35% quicker API calls, 50% shorter releases.2⃣ Helped serve worldwide research traffic; 40% speed gain through smart caching.3⃣ At Accenture, moved banking & insurance apps to microservices, cutting defects by 40%.How I stay sharp: code reviews that teach, metrics that guide, and AI pair-programming tools that free me for harder problems.Next chapter: joining a team that values clear code, steady releases, and meaningful domains. Feel like we’d build well together? Let’s talk or connect right here.
Experience
Data Analyst
Jan 2024 — Present · TX, US
Analyzed over 12 million health insurance claims monthly using SQL and Python, enabling the identification of incorrect provider billing patterns and reducing overpayments by 23%. • Designed automated dashboards in Power BI to track HEDIS and STAR quality metrics for 8 business units, accelerating compliance monitoring and reducing report turnaround time from 96 to 24 hours. • Migrated multiple legacy data pipelines to Snowflake using dbt, reducing ETL job failures by 35% and improving query performance by 2.4x on large-volume claims data. • Conducted segmentation analysis on 3 years of patient utilization data, enabling targeted outreach campaigns that increased preventative service adoption by 17% among high-risk members. • Partnered with clinical strategy teams to create cost prediction models for chronic care populations, improving forecast accuracy by 11% and influencing resource allocation decisions across 5 regions. • Deployed anomaly detection scripts in Python for eligibility and enrollment audits, identifying $6.2 million in billing anomalies within 2 quarters of implementation. • Created detailed SQL-based audit reports for regulatory submissions (CMS, NCQA), ensuring 100% data completeness and eliminating compliance penalties during Q2 and Q3 reporting cycles.
Education
University of Wisconsin-Milwaukee
Master's degree, Information Technology
St. Joseph's Degree & PG College
Bachelor's of Commerce , Information Technology
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