Aug 2025 – Oct 2025 · 2 mos · Bengaluru · Remote

• Owned Timesheets (core of the platform), streamlining resource allocation and billing accuracy boosting utilization visibility by 30% and cutting variance in billing by 20%.
• Optimized time tracking & approvals, cutting delays 25%, raising compliance 35%, and speeding approvals 40%.
• Drove roadmap via RICE & MoSCoW, reducing delivery time 20% and lifting adoption 15%.
• Partnered with finance & delivery teams, boosting forecasting accuracy 25% and increasing margin clarity 30%.

Sep 2023 – Jul 2025 · 1 yr 10 mos · Bengaluru · On-site

• As a Product Manager at Rugas Technologies, I’ve led the end-to-end product strategy and execution across three B2B SaaS platforms—Karma Tickets, Pictoral, and ViewMo—delivering measurable business impact through data-driven roadmapping, customer-centric design, and Agile execution.
• 🎟️ Karma Tickets (D2C Ticketing Platform)
• Spearheaded the mobile-first PWA redesign using UX research and user interviews, resulting in a 45% increase in engagement and 28% boost in conversions.
• Applied RICE prioritization to streamline feature scope, cutting development costs by 40% and reducing support tickets by 30%.
• Improved usability by 25% and bounce rate by 35%, positioning the platform as a top player in Canada’s D2C market with a 4.6/5 customer rating.
• 🦷 Pictoral (Dental Imaging SaaS)
• Conducted 20+ clinic interviews and market analysis, identifying a $4M+ opportunity and defining GTM strategy for a HIPAA-compliant imaging system.
• Led MVP rollout to 10+ clinics, achieving 92% feature adoption, 30% improvement in diagnostic accuracy, and 45% pilot revenue growth.
• Aligned cross-functional teams across engineering, clinical ops, and marketing to scale platform performance and ARR.
• 📺 ViewMo (Digital Display Management Platform)
• Validated cross-industry demand (retail, education, hospitality) for real-time signage solutions through stakeholder interviews.
• Authored a detailed PRD with AI-driven content tools and QR-based campaigns; roadmap prioritization (RICE + MoSCoW) accelerated MVP delivery by 35%.

Feb 2023 – Sep 2023 · 7 mos · Bengaluru, Karnataka, India · Hybrid

• At RichFeyn, I owned key product initiatives across IoT and digital platforms—blending hardware innovation with user-centered software design to deliver scalable solutions and measurable business impact.
• Led the end-to-end revamp of the company website, enhancing UX and performance to support 10,000+ active users, resulting in improved engagement and retention.
• Developed an IoT-enabled smart jar integrated with a mobile app that monitored grain levels in real time, triggering auto-notifications when inventory dropped below threshold.
• Conducted competitive analysis across 10+ direct and adjacent products, combining user insights and stakeholder feedback to shape product direction, feature prioritization, and MVP definition.
• Defined product vision, roadmap, and KPIs for a new consumer-facing offering; partnered with Engineering, Design, and Ops to launch within 3 months—resulting in a 90% increase in revenue.

Oct 2022 – Nov 2022 · 1 mo · Remote

• Designed customer journey maps, user flows, and interactive prototypes to address key drop-off points identified through bounce rate analysis—achieving an 85% acceptance rate from stakeholders and Engineering.
• Led a UX audit and synthesized user feedback into actionable product changes, resulting in a 25% improvement in website usability and reduced user friction across primary conversion paths.
• Collaborated closely with Design and Frontend teams to iterate on wireframes using tools like Figma and Notion, and monitored implementation outcomes via basic analytics dashboards.

May 2022 – May 2023 · 1 yr

Apr 2022 – Jul 2022 · 3 mos

Apr 2022 – Apr 2022 · 0 mo

• Learn Student Ambassadors are a global group of campus leaders who are eager to help fellow students, create robust tech communities and develop technical and career skills for future

Apr 2022 – Jun 2022 · 2 mos · Hybrid

• Conducted a research-driven internship focused on building predictive models for stock market movement using machine learning and natural language processing. The objective was to analyze sentiment from financial news headlines and model their influence on Dow Jones Industrial Average (DJIA) performance.
• Developed a predictive model to forecast stock movement based on sentiment analysis of Reddit’s top 25 daily financial headlines, achieving 62.7% accuracy using XGBoost, significantly outperforming the baseline of 46% from logistic regression.
• Preprocessed and combined 1989 records of historical DJIA data with headline sentiment scores; implemented text cleaning, vectorization (CountVectorizer, TF-IDF), and feature engineering using n-gram (bigram/trigram) models.
• Built and evaluated models including Logistic Regression, Naïve Bayes, Random Forest, Gradient Boosting, and XGBoost to benchmark performance.
• Visualized frequent patterns using positive/negative word clouds and interpreted polarity scores from sentiment analysis to quantify market sentiment.
• Designed a reproducible ML pipeline using Python, Scikit-learn, NLTK, and data visualization tools; documented findings for research reporting and presentation.

Feb 2021 – Mar 2021 · 1 mo · Remote

• Designed and implemented an IoT-based smart surveillance system using computer vision techniques to detect and track real-time object movement via OpenCV.
• Developed Python-based scripts for image processing and motion detection, enhancing system accuracy and reducing false positives in edge environments.
• Integrated hardware (e.g., Raspberry Pi) with vision models to create a low-latency, real-time monitoring prototype for safety applications.
• Gained hands-on experience with tools such as OpenCV, Python, TensorFlow Lite, and cloud-based logging for alert automation.

Sep 2019 – Oct 2021 · 2 yrs 1 mo

Sep 2019 – Oct 2021 · 2 yrs 1 mo