Lalit Balla

- Global CS AI, Payments, fraud & safety analytics | 80+ org | AI product measurement & decision systems - Leading a applied science organization delivering business-critical impact across payments platform, risk, compliance, fraud, safety, customer support (agent and AI-first), ecommerce, and AI Assistant product strategy, instrumentation, and north-star measurement. - Spearheading AI-driven analytics for customer support at Airbnb, owning AI Assistant success metrics, experimentation, capacity and savings models, and LLM evaluation frameworks to scale generative AI solutions that improve resolution, containment, CSAT, and cost-to-serve. - AI-powered decision science across Payments, Risk, Compliance and Fraud & Safety platforms, enhancing FX, local methods, risk friction, and payment/refund funnels while owning platform metrics, SSOT telemetry, and Safety Ops systems. - Shaping and scaling AI capabilities by building applied sciences labs where ML, agentic AI, and decision-intelligence solutions are explored, productionized, and deployed to accelerate launches, iteration velocity and insight generation.

Driving data and ML-led transformation to elevate digital customer experience and reduce support contacts through intelligent, personalized self-serve solutions—while building and scaling a high-impact analytics and machine learning team from the ground up. - Built and mentored a cross-functional team of data scientists, analysts, and ML engineers; fostering a strong delivery mindset, technical depth, and a culture of continuous learning. - Architected scalable data pipelines and semantic layers on large-scale behavioral data using modern data platforms—enabling consistent, self-serve analytics and insight democratization across product teams. - Delivered actionable business insights, product analytics, predictive models, and real-time dashboards (Tableau) that directly influenced product decisions and strategic planning. - Partnered with global product and engineering teams to deploy NLP and ML solutions using Transformers, BERT, and sequence-to-sequence models with attention—powering intelligent tagging, personalized recommendations, and dynamic content discovery through knowledge graphs. - Developed NLP and ML pipelines using BERT-based sentiment models, topic clustering, and time-series anomaly detection to surface emerging trends and product issues from social data. - Acted as a trusted advisor to product leaders and senior executives—translating data into strategic insights that informed roadmap prioritization, feature optimization, and user experience improvements. - Enabled a data-driven culture through tight integration with global teams, aligning on metrics, scaling best practices, and ensuring consistency in measurement and decision-making across markets.

Led the strategy and execution of e-commerce analytics for HP.com and B2B stores, focusing on performance measurement, revenue growth, and customer experience optimization. Collaborated closely with Category Managers and Marketing teams to define campaign strategies during key sale periods and streamline weekly merchandising operations. Managed and groomed a 17-member analytics team, fostering a culture of continuous learning, ownership, and cross-functional problem-solving. Prioritized capability-building through hands-on mentorship, upskilling programs, and exposure to high-impact projects. Successfully improved team retention and internal mobility through targeted development pathways. Enabled the team to deliver scalable analytical solutions across business performance tracking, SKU pricing and configuration, inventory management, and predictive modeling. Spearheaded the adoption of advanced statistical techniques—including regression analysis, clustering, time-series forecasting, A/B testing, and hypothesis testing—to improve the quality and impact of insights delivered. Led the integration of modern web analytics tools and frameworks, such as Adobe Analytics, Google Analytics, and Tag Manager, to deliver deep insights into user behavior. Supported initiatives like conversion path analysis, visitor segmentation, search engine marketing (SEM), and robust implementation tracking. Core tools & technologies: SQL, Python, R, Tableau, Adobe Analytics, Google Analytics, Excel, Power BI.

Defined the analytics and data infrastructure roadmap for HP’s B2B e-commerce business, with a focus on identifying high-impact analytical domains that serve as revenue levers. Built proof-of-concepts (POCs) leveraging statistical techniques such as regression modeling, cohort analysis, and segmentation to uncover revenue opportunities and optimize business performance. Led end-to-end program management of tagging implementation across B2B pages, enabling accurate data capture through Adobe SiteCatalyst and ensuring clean, actionable datasets for downstream analysis. Managed and coached a 4-member analytics team, fostering analytical rigor and solution thinking. Guided the team in conceptualizing and delivering data-driven solutions using techniques like funnel drop-off analysis, A/B testing, time-series forecasting, and customer behavior modeling.

Drive cross-functional initiatives focused on growth strategy and operational excellence across HP. Lead end-to-end project execution—from strategic planning and hypothesis formulation to execution and closure—ensuring business alignment and measurable outcomes. Leverage strong statistical and analytical expertise to validate business hypotheses using advanced modeling techniques such as linear and logistic regression, time-series forecasting, clustering, and decision trees. Skilled in designing A/B tests and causal inference frameworks to uncover actionable insights and drive data-backed decisions. Collaborate across business units to ensure data integrity, contextual accuracy, and inclusion in all analyses. Deliver strategic insights that inform executive decision-making, business prioritization, and enterprise-wide communication. Play a key role in coordinating and leading pan-HP initiatives with a deep understanding of both corporate and business unit strategies. Proficient in HP’s internal tools and methodologies, including EDW, OSRM, and proprietary analytics platforms.

Led the Sales Operations engagement for HP’s ESSN business, driving the analytics strategy and building strong stakeholder partnerships across Sales, Finance, and Business leadership. Designed and delivered data-driven solutions tailored to strategic objectives, ensuring alignment across functions. Applied advanced analytical techniques such as pipeline forecasting, sales performance modeling, segmentation analysis, and opportunity scoring. Leveraged statistical models—including linear and logistic regression, time-series forecasting, clustering (K-means), and decision trees—to uncover insights and guide sales strategy. Collaborated closely with cross-functional teams—Technology, Sales, and Finance—to ensure smooth implementation and adoption of programs. Managed and mentored a high-performing team of 7 analysts, driving excellence in sales analytics delivery across the ESSN portfolio.

Manage end-to-end delivery of key strategic projects, overseeing everything from requirements gathering and scoping to execution and delivery. Conduct in-depth secondary research to source accurate, relevant data for industry and company-level analysis. Analyze and synthesize complex data to generate actionable insights and strategic recommendations that directly address project objectives and add value to stakeholders. Skilled at translating research findings into meaningful business implications that support decision-making.

Translate complex data into actionable insights and strategic recommendations that align with project objectives and drive business value.