Harkirat Singh Chahal

Internal Data Stack & Grant Intelligence 1. Built the internal data stack powering Rhombus’s SLED (State, Local, and Education) go-to-market motion. 2. Developed a custom grant-tracking system that scrapes federal and state websites, using Google Gemini LLM for structured data extraction. 3. Designed Looker dashboards to surface nationwide funding flows and inform targeting for high-impact campaigns. 4. Supported grant-driven campaigns including: PCCD (PA), Secured School Safety Grant (IN), and School Bonds 2024 (CA). * Outcome: Drove $500K in closed-won revenue from grant-targeted outbound efforts. Paid Search (Google Ads) 1. Rebuilt the Google Ads account structure from the ground up, eliminating inefficiencies and streamlining performance. 2. Designed a custom ROAS model and led A/B testing of multiple landing pages to improve conversion rates. 3. Expanded paid search programs into Canada, the UK, and Australia to capture new market demand. * Outcome: Delivered the best-performing quarters in company history (Q1 & Q2 FY26): > +44% YoY SQLs (Q1 FY26 vs. Q1 FY25) > +32% YoY SQLs (Q2 FY26 vs. Q2 FY25) ABM & Outbound Strategy 1. Launched a coordinated ABM and outbound motion using segment analysis (Huber regression), ICP modeling, LinkedIn Ads, Direct Mail, and gamified AE outreach. 2. Operationalized AE and BDR outbound workflows, incorporating intent-based automation and follow-ups. * Outcome: > Generated $4.1M in new pipeline (Q1 + Q2 FY26) through AE outbound > Increased AE-sourced SQLs by 68% month-over-month

• Developed a strategic & tactical time series model, enabling precise forecasting for over 100 customers and significantly enhancing both long term & daily operational efficiency. • Conducted in-depth data analysis for new warehouse locations of major clients such as LEGO, Disney, Starbucks, and Apple. Emphasized feature engineering and seasonality to enhance analytics. • Facilitated seamless data integration for new accounts by implementing essential code adjustments, ensuring code reliability through extensive testing and debugging. • Played a key role in cross-functional collaboration, contributing to the development of robust data models and storytelling for management and team understanding. • Tools Used: Python, EDA, Oracle SQL, Time Series Analysis (fbProphet), Apache Airflow, Azure, CI/CD, Git.

• Developed an explainable AI model for real-time gun detection in CCTV footage to enhance public safety. • Designed a mammogram image classification system, achieving 83% accuracy in early breast cancer detection. • Leveraged technologies such as Python, TensorFlow, and Computer Vision for optimal image processing. • Utilized YOLO for instantaneous object recognition in public safety project. • Employed Transfer Learning to enhance model performance and expedite training. • Tools Used: Python, TensorFlow, Computer Vision, Image Processing, YOLO (You Only Look Once), Transfer Learning

• Project 1: Market Intelligence Tool o Led development of Market Intelligence Tool, optimizing digital spend, influencing product development, and resulting in 30+ new product launches. o Defined KPIs for Marketing, Finance, and R&D, assessing online ad impact and analyzing market trends. o Led a team creating Python web scrapers for e-commerce trend identification. o Built ML pipeline to extract relevant info from product names, resulting in 30+ launches and 15% quarterly profitability increase. o Created ranking models for SKU, improving sales prediction, and boosting digital profitability by 25%. o Integrated data insights into PowerBi dashboard for better visualization and decision-making. • Project 2: Demand Forecasting o Built time series models using fbProphet to forecast SKU requirements, optimizing warehouse space. o Implemented demand forecasting models, optimizing warehouse space and reducing logistic costs by Rs. 26 per order on average. • Project 3: M&A o Leveraged insights from Market Intelligence Tool to identify opportunities for acquiring 3 emerging skincare brands. o Collaborated with Sequoia Capital team for due diligence on prospective brands. o Presented findings on white spaces, including category, consumer base, and product propositions, for Mamaearth portfolio. • Additional Responsibilities: o Generated weekly executive reports for key decision-makers, highlighting key developments in Indian beauty ecomm space. o Authored detailed Product Requirement Documents for new features in the Market Intelligence Tool. o Conducted comprehensive research on Korean, French, and Chinese beauty companies for informed market segmentation. • Tools Used: MS Excel, Python, Scrapy, fbProphet, AWS EC2, PostgreSQL, PowerBi, NLP