Jul 2023 – Jun 2024 · 11 mos · Bengaluru, Karnataka, India · Hybrid

Mar 2022 – May 2023 · 1 yr 2 mos

• Worked as Senior Analytics Specialist in Payment Processing and Customer Success Team and handled end to end product analytics for 3 products - QR Codes, Payment Links and Smart Collect
• Independently owned BAU tasks -
• Worked on 3 new product feature launches from audience selection, defining Success to performing Impact Assessment. Helped the product by providing data driven feedback and insights that led to 2X growth in the GMV for the product
• Created Insightful dashboards to enable better consumption of data by business and set up alerts to identify unexpected metric movements. Alongside, performed RCAs on the anomalous movements that enabled business to take actions proactively
• Published weekly health metrics and conducted monthly product reviews with Head of Product and ADs
• Performed Multiple Exploratory Data Analysis to understand Product Gaps and Customer Pain Points that helped drive product strategy and improved product adoption
• Projects
• Mid Market Merchant Segmentation framework for Razorpay
• Created a framework using K-means clustering to classify Razorpay merchants into different segments. This was based on 20+ features to build personas.
• Identified and created 5 mutually exclusive segments that helped to create personalized user experiences for different merchant segments and improve customer experience
• Helped to improve the number of MTU's and GMV by 20% by improving customer experience and personalized targeting. This helped in improved retention and reduced churn
• Churn Analysis and Prediction
• Worked on Churn Analysis to solve for high churn for Payment products. Identified the top factors affecting churn and created a predictive model using Logistic Regression to tag potential Churning merchants and identify major causes for churn.
• Helped Product and Marketing by identifying the highest churning business categories and their specific pain points

Aug 2021 – Mar 2022 · 7 mos · Bengaluru, Karnataka, India

• World’s largest Home Improvement retailer (USA): Email
• Marketing Channel Analysis
• Led a team of 2 and created a framework for open rate correction
• after ios15 update. This was later scaled as standardized audience
• suppression to all CRM/email campaigns
• Integrated and analyzed data at various levels ranging from customer
• demographic data, email performance data, SKU data, sales data and
• website clickstream data for campaign measurement and assessing
• the email performance regularly through various
• KPIs(opens,clicks,$/email,conversion rate etc.)
• Drove data-backed at-scale personalization in CRM campaigns
• through
• a) Customer segmentation and A|B testing for content and audience
• strategy of email, SMS, Mobile App and direct mail campaigns
• b) Integration of probabilistic models, online recommendation
• engines, clickstream data, in-store and online purchase data, and
• campaign engagement data to drive campaign strategy
• c) Redesigning legacy reporting frameworks by incorporating
• modularized decision boards to improve decision making by
• leadership team
• Helped define audience selection strategies using data-driven
• approaches for email marketing initiatives and optimizing campaign
• performances

Oct 2019 – Jul 2021 · 1 yr 9 mos · Bengaluru, Karnataka, India

• World’s largest premium aluminum producer (UAE): Production
• Optimization
• Pot –Profitability Framework:
• Created a framework for stakeholders to understand the different pot
• behaviors pertaining to financial metrics and classify them as low or
• high performing pots using K-means clustering
• Enabled the stakeholders to have an assessment of the current state
• of any Aluminum pot in a plant with respect to the overall $ value
• (contribution)
• Consumption:
• Built a near real-time interactive dashboard to report hourly
• temperature predictions and other model outputs for each aluminum
• cell.
• Added features to identify various states in an Aluminum cell and a
• view to keep track of model accuracy enabling managers to spot
• various problems in aluminum cells on floor and monitor consumption
• of model outputs.
• Scaled the developed framework to 11 other Aluminum producing
• plants