Sep 2025 – Present · 8 mos

• Leveraged advanced AI methodologies and Big Data infrastructure to optimize the C2C Local Pickup experience, focusing on search intent, conversion drivers, and marketplace trust.
• AI-Driven Search Intent (Query Science): Developed a Query Science framework utilizing AI APIs to classify and interpret buyer search intent. Leveraged Natural Language Understanding (NLU) to map long-tail queries to high-intent local pickup categories, improving search relevance and discovery.
• Dialogue & NLP Analytics: Engineered an NLP-based analysis of anonymized buyer-seller dialogues to identify recurring patterns in transaction cancellations. Used AI-driven text mining to surface friction points in the local handoff process while maintaining strict data privacy and de-identification standards.
• Experimental Post-Analysis & Strategy: Spearheaded the post-test analysis for major A/B tests. Synthesized experimental results into strategic "callouts" that defined the hypothesis and scoping for subsequent iterative testing phases.
• Big Data Engineering (SparkSQL): Architected complex data pipelines in SparkSQL to process terabytes of unstructured behavioral data, enabling deep-dives into hyper-local supply/demand liquidity.
• Product Measurement (Tableau): Designed automated Tableau dashboards to monitor the health of the Local Pickup ecosystem, translating AI-derived insights into actionable KPIs for Product and Engineering stakeholders.

Sep 2024 – Sep 2025 · 1 yr

• Driving internal audit effectiveness through data-driven analytics, policy adherence analysis, and risk quantification
• Lead analytical assessments across diverse internal functions, rigorously evaluating the effectiveness and adherence to company policies and protocols.
• Develop hypotheses-driven audit plans by rapidly acquiring knowledge of complex internal processes, policies, and associated data structures.
• Leverage advanced analytics techniques, including statistical modeling and anomaly detection, to quantify compliance risks and policy adherence gaps.
• Built and deployed a data science model to evaluate Travel Expenses Policy adherence, distinguishing legitimate high-cost bookings from policy violations. The model analyzed booking timing, price ranges per route, and historical cost patterns to accurately pinpoint non-compliant and financially impactful instances.

Mar 2024 – Aug 2024 · 5 mos

• Built clustering engines and analytics tools to improve item fitment recall and enable self-service insights for account managers.
• Developed a dynamic clustering engine to improve part fitment recall in Vehicle Parts & Accessories search flow, leveraging hierarchical grouping, k-means clustering, and text similarity techniques.
• Designed and executed data workflows in Python, SQL, and PySpark to efficiently ingest, transform, and cluster large-scale catalog datasets.
• Created JSON-based outputs for production integration, enabling downstream indexing and improved search river item streaming.
• Applied machine learning methods to group items with shared vehicle fitments, allowing better contextualization of search results without altering existing relevance scoring logic.
• Built and published an interactive Tableau dashboard on Tableau Server for Account Managers, offering visibility into account-level and portfolio-level performance across funnel metrics.
• Enabled basic analytics self-service through intuitive filters and metrics, reducing dependency on the central analytics team for routine queries.
• Collaborated cross-functionally with product managers, engineers, and analytics leads across US and international teams, ensuring data solutions aligned with product architecture and catalog standards.

Sep 2023 – Feb 2024 · 5 mos

• Created an inventory productivity dashboard to evaluate listings and guide seller conversations using benchmarked performance metrics
• Designed and implemented the Inventory Productivity Measurement (IPM) dashboard in Tableau to unify fragmented tools and provide Category Managers with a streamlined source of truth.
• Integrated multiple data sources to track live listings, new listings, and seller performance across key brands and categories.
• Engineered performance benchmarks by clustering listings on shared attributes and behaviors, using them to identify high-performing and underperforming inventory.
• Developed performance evaluation metrics to provide directional insights into listing quality relative to peer listings within the same category.
• Enabled granular performance tracking across the entire sell funnel to support strategic guidance in Category Manager–Seller discussions.
• Created flexible filters and dynamic views to refine insights based on listing performance, seller, brand, or category.
• Collaborated with stakeholders across product, category management, and analytics to validate metrics and enhance adoption.

Mar 2023 – Sep 2023 · 6 mos

• Built buyer-to-seller onboarding strategies through behavioral analysis, conversion signals, and personalized recommendations.
• Developed data-driven targeting models to identify buyers with high potential to become successful sellers, based on purchase behavior, conversion timing, and profile attributes.
• Built segmentation logic and hypothesis frameworks to justify onboarding strategies and optimize marketing outreach.
• Designed recommendation models that suggested what and when to sell—for example, prompting users who purchased a new iPhone to list their older model.
• Analyzed hybrid users (buyer–seller) to understand their success drivers and create personalized category and pricing guidance.
• Investigated customer churn patterns by measuring retention and seller conversion rates, identifying bottlenecks and optimizing user journeys.
• Collaborated with Seller Marketing, CRM, and Lifecycle teams to embed findings into automated campaigns and personalized outreach flows.

Sep 2022 – Aug 2024 · 1 yr 11 mos

• Selected for eBay’s premier rotational program to groom future analytics leaders through four global, cross-functional assignments.
• Gained hands-on experience across Product Analytics, Seller Marketing, Internal Audit, and Decision Science teams.
• Delivered end-to-end analytics solutions using Python, SQL, Tableau, and PySpark—ranging from clustering models to performance dashboards.
• Partnered with stakeholders across Product, Finance, and Strategy to shape data-informed decisions.
• Developed a strategic lens on eBay’s global business, enabling faster ramp-up, domain agility, and structured problem solving.

Sep 2022 – Feb 2023 · 5 mos

• Built frameworks and tools to improve seller engagement, optimize marketing visibility, and evaluate on-site behavior.
• Developed frameworks and tools to enhance seller engagement and optimize marketing visibility at eBay.
• Created a rule-based model to classify sellers, significantly boosting engagement and driving GMV.
• Designed an automated Marketing Scorecard dashboard, streamlining access to core marketing metrics.

Apr 2021 – Sep 2022 · 1 yr 5 mos

• Delivered insights on business performance through cross-functional KPI modeling, executive dashboards, and advanced scenario analytics.
• Developed driver-based business models to forecast operational KPIs such as active users, conversion rates, churn, and customer lifetime value (CLV).
• Built automated dashboards using Tableau and Excel to track performance across product, marketing, and sales funnels.
• Collaborated with Product, Ops, and Marketing stakeholders to translate business problems into analytical frameworks and track their leading indicators.
• Conducted root cause and variance analysis on business performance vs. expectations, highlighting trends in buyer/seller behavior, geography, and seasonality.
• Led metric governance by defining, auditing, and standardizing KPIs used across teams for consistent enterprise-level reporting.
• Created self-service tools and frameworks to reduce ad hoc analysis burden and improve speed of insight delivery to leadership.
• Acted as a strategic thought partner in cross-functional planning sessions, supporting decision-making through structured data storytelling.

Dec 2017 – Apr 2021 · 3 yrs 4 mos

• Corporate FP&A - Global Business Performance
• Awards
• Received multiple Spot Awards from Immediate Superior, Sr Director and CFO
• Cadences
• Preparing communication about Performance and key call-outs for Senior Executives and Board
• Members
• Analytics
• Function as a liaison across multiple product domain teams, across multiple geographies and take
• ownership of tracking their respective and collective progress
• Run weekly cadences for Global Performance reports
• Slice and dice weekly performances, bring to attention the key drivers and critical metrics
• Sizing impacts and opportunities based on environmental, macroeconomic and competitive actions