+ <p class="details-description">Joined as the 7th hire at this Y Combinator-backed cleantech startup, playing a pivotal role in scaling analytics infrastructure during rapid company growth. Evolved through three progressive roles over the course of the journey, from individual contributor to technical team lead, driving end-to-end development of advanced predictive analytics algorithms across multiple domains including system fault detection, performance degradation analysis, and environmental forecasting models. Currently spearheading a cross-functional team of 5 data scientists and analysts in architecting a next-generation fault detection engine, delivering measurable business impact through 30% runtime optimization and enhanced predictive accuracy. Developed LLM-based internal reporting automation, streamlining operational workflows and reducing manual analysis overhead. Championed the adoption of test-driven development practices across the data science organization, establishing robust code quality standards and deployment reliability. Key technical contributions span machine learning pipeline development, time-series forecasting, anomaly detection algorithms, and scalable data processing systems supporting real-time monitoring of renewable energy assets. Collaborated closely with product managers, data engineering teams, and business stakeholders to translate complex analytical insights into actionable business intelligence.</p>
0 commit comments