Rishita Meharishi

AI brain of the Go-to-Market team. Turning messy data into actionable insights. Built and deployed a suite of AI-powered GTM automation tools using Python, JavaScript, HTML, Claude API, and RAG, etc Engineered data pipelines and account intelligence workflows across Salesforce, ZoomInfo, Marketo, and Gong Won in Obsidian's internal AI hackathon; collaborated with the engineering team to build an LLM-powered DSL Copilot that turns natural language threat queries into production-ready security rules in seconds. Led customer discovery interviews with TAMs, owned the UI/UX, and co-presented to company leadership. The tool is now actively used and heavily appreciated by the TAM team. Conducted deep-dive data analysis of 1,300+ Gong calls (ENT vs. MM) to surface Agentic AI trends, competitive patterns, and prospect pain points, delivering clean, digestible, and actionable insights.

Partnered with a 10-person cross-functional team to translate client needs into prompt-engineered product scenarios using Cursor and HTML prototypes, improving feature clarity and delivery speed. Designed and executed QA and testing workflows, reducing redundant review cycles through better scenario coverage and reproducible edge case documentation. Authored and maintained technical documentation for the Reddy LMS, establishing clear developer onboarding guides and standardizing knowledge transfer across teams. Technical documentation: https://docs.reddy.io/manual/reddy_lms_overview

Promoted events, expanded networks, and secured sponsors for hackathons and career fairs, impacting 1000+ students.

Supported the Speech, Language, and Hearing Sciences department by managing technical operations. Resolved over 100+ student issues related to enrollment systems and LMS platforms, ensuring timely assistance. Collaborated with 7+ faculty members to enhance LMS setup, promoting efficient course delivery and academic services.

Provided technical guidance to a class of 45+ students: graded tests, coding labs, and assignments for the entire semester. Explained technical concepts in simple words and conducted office hours.

Authored a 5-page research paper in LaTeX on AI model evaluation and LLM inference pipelines, serving as a technical reference for collaborators. Optimized Random Forest regression models for fusion plasma modeling, improving predictive accuracy and reliability. Built Python pipelines to save, restore, and benchmark trained models using metrics such as MSE, MAE, and R2. Partnered with 5+ MIT faculty to refine research methodologies and streamline analysis workflows

Developed and maintained product roadmap, aligning cross-functional teams around B2C user needs Led product discovery by identifying user pain points by conducting 50+ customer discovery interviews and translating them into high-impact, actionable features Managed the full product lifecycle from ideation to launch, delivering features that boosted engagement and trust Defined and tracked key success metrics using data insights to guide product decisions and feature prioritization Aligned product planning with business objectives through strategic thinking and cross-functional collaboration

Delegated 50+ students in learning physics concepts and enhanced the in-class learning experience by working closely with the instructor and faculty.

Developed company website using HTML, CSS, JavaScript, and SQL to improve traffic and UX Collaborated with UX designers and Product Managers on requirements Designed and executed data analysis pipelines using SQL to keep track of users

magna cum laude