Hema Radhika Reddy

I’m a Production Analyst Trainee who turns production data into actionable decisions through monitoring, anomaly detection, and structured reporting. I enjoy making complex systems easier to understand by translating metrics and incident patterns into clear insights.

In my trainee role, I monitored and analyzed production data trends, system metrics, and incident patterns, and I automated recurring analytical tasks using Python. By improving log parsing and metric extraction workflows, I reduced manual effort by 25% and increased reporting accuracy.

My projects reflect my AI-and-data engineering focus: I built a GenAI-powered assessment recommendation engine using FastAPI, LLMs (Gemini API), and semantic similarity with Sentence-BERT embeddings. I also developed scalable analytics in Hadoop/MapReduce with Scala and designed a DRL framework for real-time ad placement using DQN, A2C, and PPO.

I’ve published 2 international conference research papers in AI and Computer Vision, and I actively strengthen my fundamentals by solving 270+ problems on LeetCode. I’m motivated by environments where I can ship data-driven products, improve pipeline reliability, and continuously learn from real-world feedback.