Kiranmai

Python-focused engineer with 5.5 years across operations analytics, data systems and backend development — including work on data feeding ML-driven dispatch systems at Uber and a full-stack civic platform built solo. Currently completing the PG Program in Data Analytics & AI at NIELIT (Govt. of India), covering Machine Learning, Deep Learning, NLP and Generative AI. Self-directed, comfortable with ambiguity, and looking to go all-in on building AI/ML systems in a small founding team.

Data & Operations Analyst — ML Systems & AI - Uber - Hyderabad, India

(2023-05 - 2025-11)

• Worked on large-scale ride-booking, dispatch and driver-allocation data feeding Uber's ML-driven dispatch and ETA prediction systems — investigating anomaly patterns, model output deviations and data drift in production.
• Built validation and pattern-detection logic in Python and SQL across geo-location, time-of-day and demand signals — feature-engineering-adjacent work that surfaced quality issues in upstream training and inference data.
• Performed root cause analysis on production KPI deviations (booking success, ETA accuracy, error rates) and partnered with engineering and product teams to ship fixes.
• Automated repetitive validation pipelines using Python, cutting manual QA effort on critical ML-adjacent workflows.
• Explored LLM-based summarisation for internal incident reports using Python and the OpenAI API — built a prototype that auto-summarised long RCA documents into structured formats, reducing review time for the ops team.
• Studied prompt engineering and Generative AI concepts as part of ongoing upskilling — applying learnings to automate repetitive text-heavy reporting tasks within the team.
• Operated in an ambiguous, fast-moving environment — picked up unfamiliar tools, scoped own investigations and shipped without waiting for handed-down tickets.

Ward Education & Data Processing Secretary - Govt. of Andhra Pradesh - Andhra Pradesh, India

(2019-10 - 2023-09)

• Owned end-to-end data operations for 800+ students across 12 schools — built structured reporting workflows using Python and Excel, going from paper registers to clean datasets to district-level MIS submissions.
• Prepared monthly MIS reports for the District Education Officer covering attendance trends, dropout rates, welfare scheme utilisation and demographic breakdowns — automated report generation using Python (pandas), adopted as standard inputs to district review meetings.
• Analysed scheme enrollment and attendance data using Python to identify underutilisation patterns across student groups; flagged gaps that led to targeted outreach in 3 villages and measurable improvement in enrollment.
• Designed validation, reconciliation and cross-check logic in Python for data collected across 6 government welfare programs, ensuring accurate and audit-ready submissions for district reporting cycles.
• Sole data point of contact for the District Education Officer — figured out reporting workflows independently, coordinated with 12 schools and resolved escalations without a playbook.

PG Program in Data Analytics & AI - Data Analytics & Artificial Intelligence - NIELIT, Calicut (Govt. of India) (2025-10 - 2026-04)

B.Tech - Computer Science & Engineering - Vignan's Lara Institute of Technology and Science, JNTUK