- Developed Excel and Google Sheets models for deal sizing, enabling multi-million dollar comparisons against competitors like AWS Backup; migrated these models to Salesforce CPQ for enhanced tracking.- Collaborated with engineers to establish a central data lake in Snowflake, integrating customer usage data from AWS DynamoDB and RDS, and importing data from Salesforce and Zendesk using StitchData.- Created a robust data warehouse by cleaning and joining raw JSON product data with other sources, and built interactive dashboards in AWS QuickSight to provide the GTM team with insights on customer health, usage patterns, and upsell opportunities.- Designed a data analytics pipeline to analyze multi-million dollar AWS bills, resulting in cost optimizations of over $500K/year, and worked with PMs to refine pricing strategies based on profit margins.- Established revenue recognition models for a consumption-based business, accurately tracking ARR, churn, and upsell/downsell metrics.

- Strategized the launch of Netflix Games, conducting comprehensive market research to evaluate industry opportunities.- Analyzed anonymized viewing data to provide recommendations based on device usage patterns, genre preferences, and geographic viewing trends to predict propensity to new service adoption.- Developed customer segments based on streaming activities, proposing tailored advertising strategies for mobile gamers to enhance engagement.

- Coordinated the Athletics Tutoring Program, providing administrative support for daily operations, including scheduling student-athlete tutoring appointments, tracking attendance data, and preparing comprehensive reports.- Automated the generation of daily, weekly, and quarterly reports and dashboards using Excel (VBA, VLOOKUP, Pivot Tables) and web scraping, reducing report preparation time from 20 hours to 40 minutes.- Calculated usage metrics to optimize staffing hours and tutor enrollment, enhancing program efficiency.- Self-taught in AppleScript and implemented a solution to auto-fill and submit web forms, decreasing the required time from 25 hours to 4 hours.

- Developed customer personas and mapped customer journeys, identifying key campaign strategies and optimal communication channels to enhance engagement.- Processed and analyzed large datasets exceeding one billion rows using R, PySpark, and SQL, creating predictive models to mitigate customer churn.- Utilized market basket analysis and association rules to uncover insights into customer interactions with AT&T, forecasting potential future behaviors.- Recommended strategic actions and ideal contact timings to boost customer engagement and minimize churn risks.

- Analyzed product formulations to optimize product line selection, identifying the most profitable variations to drive revenue.- Conducted in-depth research and implemented optimization strategies across various scenarios, including supplier selection, procurement processes, fulfillment center location, freight allocation, project crashing, and the traveling salesman problem, utilizing AMPL and CPLEX.- Processed 400,000 data points to define parameters for a linear regression model, assessing customers’ perceived importance of different product features, and implemented the model using R.

- Estimated demand for out-of-stock products using the Universal Singular Value Thresholding (USVT) algorithm, implemented in Python (NumPy, Pandas, Scikit-learn, Matplotlib).- Applied Monte Carlo simulations to assess the impact of stocking levels on profits and modeled customer behavior to estimate lifetime value using Microsoft Excel.- Performed data analysis for one of India’s leading online grocery apps, serving 10 million users. Developed custom R functions (dplyr, ggplot2) that significantly reduced data preparation and exploration time for 12 million data points.

- Led a team of 30 professionals to design and implement a perception and feedback study, engaging over 4,000 respondents.- Collaborated with clients, including shareholders and C-level executives from one of India’s largest conglomerates (market cap: $200 billion), to pinpoint critical issues.- Compiled and analyzed 1.6 million qualitative and quantitative data points using IBM SPSS to uncover meaningful patterns.- Generated comprehensive reports and actionable recommendations utilizing MS Office (Excel, PowerPoint, Word), presenting findings effectively to clients.- Directed a multidisciplinary team of developers, UI designers, and legal experts in the development of a SaaS product for data collection and analysis, recommending key features, APIs, and cloud infrastructure, while creating a thorough product manual.