Aug 2023 – Present · 2 yrs 10 mos · San Jose, California, United States

• 𝐂𝐌𝐏𝐄 𝟏𝟐𝟎: 𝐂𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐎𝐫𝐠𝐚𝐧𝐢𝐳𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞 - 𝐏𝐫𝐨𝐟 𝐁𝐡𝐚𝐰𝐚𝐧𝐝𝐞𝐞𝐩 𝐒𝐢𝐧𝐠𝐡 𝐇𝐚𝐫𝐬𝐡 - (𝐉𝐚𝐧 𝟐𝟎𝟐𝟒 - 𝐏𝐫𝐞𝐬𝐞𝐧𝐭)
• Conducted lab sessions focused on the structure and function of the CPU, instruction sets, and GPU design.
• 𝐁𝐔𝐒𝟑 𝟏𝟓𝟎: 𝐅𝐮𝐧𝐝. 𝐨𝐟 𝐇𝐮𝐦𝐚𝐧 𝐑𝐞𝐬𝐨𝐮𝐫𝐜𝐞 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 & 𝐁𝐔𝐒𝟑 𝟏𝟓𝟑: 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐨𝐟 𝐃𝐢𝐯𝐞𝐫𝐬𝐢𝐭𝐲 - 𝐏𝐫𝐨𝐟 𝐃𝐫. 𝐘𝐞𝐨𝐧𝐤𝐚 𝐊𝐢𝐦 - (𝐉𝐚𝐧 𝟐𝟎𝟐𝟒 - 𝐏𝐫𝐞𝐬𝐞𝐧𝐭)
• Conducted research on developing course materials covering HR diversity management, cross-cultural communication, and compliance frameworks to enhance student understanding and engagement.
• 𝐁𝐔𝐒𝟐 𝟏𝟑𝟎: 𝐈𝐧𝐭𝐫𝐨 𝐭𝐨 𝐌𝐚𝐫𝐤𝐞𝐭𝐢𝐧𝐠 - 𝐏𝐫𝐨𝐟 𝐃𝐫. 𝐒𝐞𝐫𝐤𝐚𝐧 𝐒𝐚𝐤𝐚 - (𝐀𝐮𝐠 𝟐𝟎𝟐𝟒 - 𝐏𝐫𝐞𝐬𝐞𝐧𝐭)
• Supported faculty in delivering lectures on the strategic control of marketing efforts and understanding social and ethical responsibilities in marketing.
• 𝐏𝐇𝐘𝐒 𝟐𝐁: 𝐅𝐮𝐧𝐝. 𝐨𝐟 𝐏𝐡𝐲𝐬𝐢𝐜𝐬 - 𝐏𝐫𝐨𝐟. 𝐃𝐫 𝐌𝐚𝐱𝐢𝐧𝐞 𝐒𝐡𝐚𝐨 - (𝐀𝐮𝐠 𝟐𝟎𝟐𝟒 - 𝐏𝐫𝐞𝐬𝐞𝐧𝐭)
• Facilitated student learning in electricity, magnetism, optics, and atomic structure through interactive discussions and hands-on problem-solving.
• 𝐁𝐔𝐒𝟐 𝟏𝟗𝟎: 𝐅𝐮𝐧𝐝. 𝐨𝐟 𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 - 𝐏𝐫𝐨𝐟 𝐃𝐫. 𝐃𝐚𝐯𝐢𝐝 𝐌𝐜𝐅𝐞𝐞𝐥𝐲 - (𝐀𝐮𝐠 𝟐𝟎𝟐𝟒 - 𝐃𝐞𝐜 𝟐𝟎𝟐𝟒)
• Assisted in teaching quantitative models and data-driven decision-making techniques used in business analytics.
• 𝐌𝐀𝐓𝐇 𝟏𝟒𝟑𝐂: 𝐍𝐮𝐦𝐞𝐫𝐢𝐜𝐚𝐥 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬 𝐚𝐧𝐝 𝐒𝐜𝐢𝐞𝐧𝐭𝐢𝐟𝐢𝐜 𝐂𝐨𝐦𝐩𝐮𝐭𝐢𝐧𝐠 - 𝐏𝐫𝐨𝐟 𝐌𝐨𝐡𝐚𝐦𝐦𝐚𝐝 𝐒𝐚𝐥𝐞𝐞𝐦 - (𝐉𝐚𝐧 𝟐𝟎𝟐𝟒 - 𝐌𝐚𝐲 𝟐𝟎𝟐𝟒)
• 𝐂𝐒 𝟏𝟓𝟖𝐀: 𝐂𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐍𝐞𝐭𝐰𝐨𝐫𝐤𝐬 - 𝐏𝐫𝐨𝐟 𝐃𝐫. 𝐅𝐚𝐫𝐚𝐦𝐚𝐫𝐳 𝐌𝐨𝐫𝐭𝐞𝐳𝐚𝐢𝐞 - (𝐉𝐚𝐧 𝟐𝟎𝟐𝟒 - 𝐌𝐚𝐲 𝟐𝟎𝟐𝟒)
• 𝐌𝐀𝐓𝐇 𝟏𝟔𝟑: 𝐏𝐫𝐨𝐛𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐓𝐡𝐞𝐨𝐫𝐲 - 𝐏𝐫𝐨𝐟 𝐓𝐚𝐡𝐢𝐫 𝐈𝐬𝐬𝐚 - (𝐒𝐞𝐩 𝟐𝟎𝟐𝟑 - 𝐃𝐞𝐜 𝟐𝟎𝟐𝟑)

Aug 2023 – Dec 2024 · 1 yr 4 mos · San Francisco Bay Area · Hybrid

• At Hail UFO, I focused on understanding consumer behavior and building data-driven personalization across our platform. My work centered around improving our recommendation engine and its influence on customer buying patterns. I analyzed how our algorithms impacted customer choices and broader business metrics.
• Developed buying propensity machine learning models to identify high-intent users, improving marketing ROI by 24% and increasing monthly sales.
• Built predictive models to assess style performance, helping the merchandising team reduce overstock by 1,500 units per season and streamline inventory planning.
• Created targeting models for personalized offers, resulting in a 1.7x increase in promotional campaign effectiveness.
• Conducted A/B and multivariate testing on campaign creatives and landing pages, increasing lead-to-purchase conversion rates by 15%.
• Created predictive dashboards for marketing KPIs such as CAC, ROAS, CLTV/CAC ratio, and funnel drop-offs, enabling real-time performance tracking and agile campaign decisions.

Sep 2021 – Aug 2023 · 1 yr 11 mos · India

• As a Data Scientist, GTM & Strategy at Samsung, I contributed to strategic decision-making and optimized business processes by developing and deploying machine learning models, driving impactful results across various initiatives.
• Improved CRM marketing strategies by 12% by developing predictive models in Python and SQL to assess customer propensity for newly launched products, providing actionable insights into customer behavior and driving targeted engagement.
• Boosted next-purchase recommendations by 25% by deploying an ALS-based recommendation engine on the Samsung eCommerce website, personalizing recommendations through analysis of customer transaction history and enhancing user engagement.
• Contributed to over $150Mn in incremental revenue by building go-to-market strategy models for flagship launches like the Z Series, S22, S23, and Watch5, driving an 8% increase in Y-o-Y conversion rates and a 20% boost in customer retention.
• Reduced churn and improved retention by 10% by designing and implementing a customer loyalty tracker, enhancing behavioral analysis to identify high-risk customers and optimize retention efforts.
• Optimized marketing decision-making by creating dynamic dashboards in Tableau and Power BI, analyzing large datasets to refine campaign strategies and enhance business performance.
• Increased operational efficiency by 20% by collaborating with cross-functional teams to build comprehensive dashboards and presentations for senior leadership, summarizing key product metrics (Web/App) at a corporate level.
• Developed and maintained expertise in Samsung's key customer segments, and provide insights back to Product Marketing teams that result in improved product capabilities.
• Collaborated with product marketing and cross-functional team on new product launches, quarterly product releases and post-release optimizations.

May 2020 – Aug 2020 · 3 mos · Singapore

• At Varidus, a Singapore-based Venture Builder, I played a key role in driving investment strategy and improving decision-making processes through data analysis and predictive modeling.
• Improved prediction accuracy by 18% by analyzing global startup mergers and acquisitions data and utilizing predictive modeling techniques to forecast merger potential, providing more reliable insights for investment strategies.
• Enhanced investment decision-making by 15% by collaborating with the Venture Capital team to create data-driven pitch decks, leveraging insights from the VentureCapInsights database to guide investments across a portfolio of 50+ startups.
• Provided valuable insights for venture capitalists by designing and implementing predictive models to assess and monitor potential mergers, supporting strategic investment evaluations and identifying high-value opportunities.
• Identified key growth opportunities by preparing financial and market analysis of specific geographic areas, assessing their attractiveness for expansion and investment.
• Extracted trends and insights from financial data by identifying patterns in startup distributions, funding amounts, company stages, and investment patterns across different regions, guiding informed investment decisions.
• Assessed competitive dynamics in emerging sectors by conducting research on the effects and trends in industries like FinTech, Blockchain, AI, Logistics, SaaS, and EdTech, with a specific focus on South East Asian markets.

Apr 2020 – Jun 2020 · 2 mos · India

• At SenseGrass, I contributed to the development of cutting-edge technology to enhance sustainable farming practices through machine learning and data-driven solutions.
• Boosted crop yield by 15% for targeted regions by leading the development of machine learning systems that utilized remote sensing indices to predict sustainable farming practices, driving more efficient agricultural outcomes.
• Refined precision agriculture strategies by 20% through statistical analysis of NDVI images, optimizing resource usage and enabling farmers to maximize crop growth with more accurate, data-driven decisions.
• Improved decision-making for precision agriculture by collaborating with agronomists and data scientists to develop remote sensing models, enhancing the accuracy of sustainable farming predictions.
• Conducted in-depth research on evapotranspiration, utilizing resources like the FAO and USGS to deepen the understanding of sustainable farming practices and enhance prediction models.
• Developed a robust web crawler to systematically scrape Native Plant Nursery data from the Michigan Native Plants database, enriching the dataset for more comprehensive agricultural analysis.

May 2019 – Jul 2019 · 2 mos · Kolkata Area, India

• Worked on Image processing algorithms in OpenCV (Python).
• o Learned to apply different Geometric transformations.
• o To convert images to binary images using Thresholding.
• o Smoothing images with custom kernels.
• o Applying Morphological and Hough Line transformation.
• o Learned to find image gradients, edges with Canny Edge Detection.
• o Image Segmentation with Watershed algorithm.
• Hands on Computer Vision techniques including Modelling and Perspective projection, Coordinate
• transformations, Camera calibrations, Epipolar geometry, Harris corner formulation, Histogram of Oriented Gradient (HOG) feature etc.
• Implemented Modelling, Rendering, Animation, Fast algorithms, Boundary filling algorithms, Polygon meshes, Hidden-Surface removal, Phong illumination model, Gouraud and Phong shading algorithms in Computer Graphics.
• Environment: Python, MS Excel, OpenCV, 3D-Zephyr.