• Inform and inspire the product development to create leading user experience. Develop core decision-impacting metrics, economic models capturing supply and demand relationships, research economic interventions for use in specific Yelp products and features• Facilitate collaborative relationships with product owners to identify key hypotheses, design, plan, engineer and execute appropriate experiments, and advise on product decisions with economic analyses and data product improvements• Demonstrate impact and recommend solutions to economic problems to senior leaders and cross functional groups and advocate for additional investment where needed• Own the team’s stakeholder engagement model, defining and communicating the decision criteria for committing team resources• Engage and recruit high quality talents to foster both team and employee growth

• Build and lead a high performing team of 10 data scientists, creating quantitative analysis and statistical model predictions (e.g. gradient boosting machine) that provide insights on customer behavior and profitability dynamics. The analytical outcomes are adopted as core decisioning factors that shape and refine product design impacting millions of customers and billions of business value• Lead end to end high impact DS project with stringent product requirements by owning entire problem space, from data, modeling to processes and tooling; recently delivered project improving model prediction accuracy by 20%, generating 30% increase in lifetime value• Drive forward product management of credit decisioning by owning the initiative, regularly reporting to and aligning with VPs and C‑level. Collaborate closely with engineers, product managers, strategy and operations teams to define and solve business problems through analytics, reports, models and A/B tests• Monitor the stability of credit risk, revenue and valuation models rigorously. During COVID‑19, led simulation analysis to determine model performance degradation with observed trends in market; implemented COVID‑19 related credit strategies and alternative product designs to adapt to the evolving macroeconomic environment• Active in talent recruiting and training, built and developed associates’ job specific skills of predictive modeling, statistical analysis, experimentation and test design, and credit risk management

• Led cross‑functional team of 5+ data scientists and business analysts to monitor credit risk and market trends, set live updated dashboards to regularly report portfolio health for over millions of customers with billions of business impact• Worked with Equifax and Transunion, internal tech and legal teams to order, transfer and validate data covering over 4000+ raw variables for millions of customers to enhance data infrastructure and predictive modeling capabilities• Designed model scoring package with AWS micro‑services/docker API and deployed it real time in cloud, reducing processing time by over 50%• Delivered internal and external (US and Canada) audit commitments on model and credit governance• Facilitated DS recruiting process covering initial assessment and further technical interviews, designed job specific SQL, python and modeling questions to update test bank• Focused on associate engagement, diversity and inclusion and women in tech initiatives for 110+ associates enterprise wise

• Owned 6 customer behavior models as products, led related analytical and modeling work to assess business value and implement the recommendations to refine product design in customer acquisition and management spaces• Designed A/B tests to define new product, leveraged learnings collected from the tests to solve complex business problems and launch new credit strategy• Ramped up junior associates and interns on model development and other DS skills• Converted, validated and monitored credit risk models with migrations in data source, language (SAS to Python) and platform (on‑premise to cloud) by adopting a combination of coding skills involving Python, SQL, Shell and SAS• Created data visualization with R Shiny and launched the tool on AWS EC2 to monitor portfolio performance worth billions of exposure

• Developed and implemented PD/EAD/LGD model part of the Basel II Implementation Program of retail models for US and Canadian portfolios covering billions of dollars of exposure• Performed ongoing refinement and monitoring post implementation of the modelswith tens of millions of records processed, and updated model health rating to senior stakeholders on regular basis• Documented model development process including data cleaning, methodologies assessed, modeling recommendations, analytic results and collaborated with model validation and implementation teams to deploy the models• Assessed modeling methodologies and approaches for retail credit risk and worked with business teams for profit and loss analyses

Courses covered as a Teaching Assistant Introduction to Microeconomics, Statistics for Economics, Intermediate Macroeconomics, Introductory Econometrics I, Econometric Methods (Graduate), Econometric Methods on Time Series (Graduate)Courses covered as an Associated InstructorIntermediate Macroeconomics Statistics for Economics

As a Research AssistantWorked for Professor Barry Jones, solved linear and nonlinear programming problems in MATLAB, Excel, etc.Courses covered as a Teaching AssistantPrinciples of Microeconomics