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Sumedh Reddy Katta
GitHub

Sumedh Reddy Katta

@sumedhreddy-web

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About

Data Analyst & Engineer | Python • SQL • Hadoop • Tableau | Bridging analytics & business impact.

Followers 0
Following 0
Public Repositories 35
Expertise

Skills & Technologies

Python
GitHub Work

Projects & Repositories

Recent public projects and repositories from this profile.

Vendor-Selection-Onboarding-Process-Redesign

Python

Led a mock RFP evaluation comparing 3 vendors on weighted criteria and 3-year TCO, recommending a clear winner on both dimensions. Redesigned vendor onboarding, cutting handoff steps from 11 to 2 (82% reduction), and built a 13-story implementation backlog across 3 sprints.

⭐ 0 Forks: 0

Invoice-to-Contract-Reconciliation-Pipeline-AWS-

Python

Built a serverless AWS pipeline (Lambda, S3, DynamoDB, EventBridge, SQS) that automatically reconciles vendor invoices against contract rates, routing discrepancies for review. Validated the pipeline with real boto3 calls, catching and fixing a Lambda configuration bug before deployment.

⭐ 0 Forks: 0

Contractor-Workforce-Planning-Model

Python

Developed a contractor workforce forecast in Excel projecting quarterly headcount and spend against budget, with a live scenario toggle (Base Case, rate increase, hiring freeze) recalculating budget runway automatically. Modeled contractor-vs-FTE cost tradeoffs across 5 roles.

⭐ 0 Forks: 0

Contract-Renewal-License-Optimization-Analysis

Python

Identified $235,881 in potential annual savings by analyzing license utilization and renewal timelines across 35 technology contracts. Built a SQL and Python pipeline flagging consolidation opportunities, with migration-cost-adjusted savings excluding categories where consolidation didn't pay off.

⭐ 0 Forks: 0

Technology-Vendor-Performance-Scorecard

Python

Built a Power BI vendor scorecard (Power Query, DAX) ranking 20 technology vendors on SLA, cost, and incident KPIs. Designed a weighted scoring model with an automatic critical-incident override, flagging 5 underperformers, and delivered a cross-validated Excel dashboard and QBR deck.

⭐ 0 Forks: 0

Microbiology-Genomics-Spark-Analytics

Python

Trained a Spark MLlib model predicting antimicrobial resistance from bacterial genomic markers (0.876 AUC), with feature importances validating against known AMR biology. Built surveillance-trend analytics detecting a rising carbapenemase-resistance signal across a 3-year isolate dataset.

⭐ 0 Forks: 0