Bengaluru, Karnataka, India
I’m a Data Analyst and Decision Scientist with 5+ years of experience transforming raw data into strategic, scalable impact across product, growth, and customer success teams. At Rippling, I led analytics initiatives that improved CSAT from 85% to 95%, migrated high-cost Salesforce views to dbt/Snowflake (80% cost savings), and built self-serve dashboards for Support KPIs streamlining performance tracking and reporting across the org. At Toplyne, I automated customer reporting pipelines, saving 2 weeks of manual work, and created visibility into model performance for Customer Success Managers—reducing churn and boosting trust. I also standardised onboarding pipelines for 12+ customers, helping scale operations with minimal ad hoc effort. Previously at Jumbotail, I designed a gamification strategy that increased order frequency by 25% and click-through rates by 20% by optimising product discovery, recommendation logic, and engagement loops. I’m proficient in SQL, Python, dbt, Tableau, and Snowflake, and I thrive at the intersection of data engineering and analytics—bringing structure to chaos, clarity to metrics, and momentum to decisions. I care deeply about solving the right problems with data and helping teams move fast without breaking trust.
Toplyne - Data Analyst (Customer Success) * Empowering Customer Journeys with Data: Played a pivotal role in onboarding customer data from sources like Mixpanel, Amplitude, Salesforce, and HubSpot. Standardized data within Snowflake, creating a solid foundation for data science exploration. Tools used: Snowflake, ETL, SQL, Python. * Automated Reporting & Insights: Developed automation pipelines to generate and distribute customer reports via channels like Slack and email, significantly reducing man-hours and costs. Tools used: Python, Slack API, ETL processes. * Championing Customer Success: Enhanced visibility for Customer Success Managers by creating reporting systems with high accuracy and low latency, leading to reduced customer churn and increased trust. Tools used: Tableau, SQL. * Onboarding Expertise: Successfully onboarded 10+ customers, each with unique data schemas and business needs, ensuring smooth transitions and standardized solutions. * Contribution to Innovation: Actively contributed to the development of an internal query builder by optimizing SQL functions, driving efficiency across data engineering workflows.
Automated creation and distribution of customer reports across Slack, email, and Telegram — saving 2 weeks of manual effort per cycle and reducing operational costs. Onboarded 12+ customers with diverse data sources into Snowflake, building standardized schemas that eliminated repeated ad hoc work by the data science team. Created model performance and failure alert dashboards for Customer Success Managers, preventing churn and increasing product trust. Contributed SQL functions to the internal query builder, improving performance for the Data Engineering team.
Jumbotail - Decision Scientist (Data Science) * Driving User Engagement through Gamification: Led the development of gamification features in the Jumbotail app, boosting order frequency by 25% and visits by 10%. Utilized insights to shape user habits and foster loyalty. Tools used: Python, SQL, App Analytics. * Data Quality and Behavior Analysis: Collaborated with tech teams to improve data quality, giving clearer insights into customer behavior and enhancing product sorting and notifications. Tools used: AWS Redshift, EC2, SQL. * ML for Better Decision-Making: Developed machine learning models to predict optimal customer hubs, as well as recommendation systems for product suggestions, which improved conversion rates and product discovery. Tools used: Machine Learning (Python, Scikit-learn), AWS. * Campaign Attribution and Funnel Insights: Carried out comprehensive analysis on campaign funnels, enabling business teams to target effectively and achieve better GMV attribution. Tools used: Tableau, Google Sheets, SQL.
Developed and shipped a gamification product driving a 25% increase in order frequency and 10% rise in user visits by creating a habit loop within the app. Designed product sorting algorithms and personalized recommendations, increasing conversion rates by 15% and product views by 30%. Led campaign funnel analysis and automated data flows to Google Sheets and Redshift, reducing Redshift load by 15%.
Pyxis - Data Analyst (Pyxis Insights) * Brand Analysis on Social Platforms: Conducted detailed data analysis on brand studies across platforms like Instagram and Facebook, helping clients understand their brand impact. Tools used: Python, Tableau. * Scraping and Automation for Efficiency: Automated processes and scraped data from LinkedIn, reducing client acquisition effort by 50 times and generating valuable ad hoc insights. Tools used: Python, Web Scraping.