Dhruv Sharma

About Dhruv Sharma

As a Senior Risk & Fraud Data Analyst, I specialize in trust and safety, fraud detection strategy, and cross-functional program delivery across digital onboarding and payments. With over 6 years of experience in risk analytics, technical program management, and data science, I drive scalable fraud controls that balance customer experience, operational impact, and business risk.Key Initiatives & Impact- Fraud Strategy & Detection Programs – Led the design and rollout of multi-layered fraud control strategies including device intelligence, SSA-deceased logic, AAMVA DL scan integration, and velocity-based synthetic ID detection. Resulted in $50M+ in protected revenue and over 99% confirmed restriction accuracy in high-risk flows like CPC and Secure Checking- Trust & Safety Program Leadership – Developed frameworks to detect identity fraud, bot-driven onboarding abuse, and social-engineered Zelle cashouts. Partnered with Ops, Legal, Engineering, and Product to build real-time response pipelines and feedback loops that strengthened trust infrastructure and reduced manual review load- Cross-Functional TPM Execution – Owned end-to-end program lifecycle from fraud signal identification to detection logic implementation across fraud systems. Led fraud/TPM cadences across Engineering, Fraud Ops, and Risk Policy to ensure alignment across strategic rollouts and real-time abuse response- Data-Informed Decisioning – Built fraud detection telemetry dashboards and audit tools that enabled live tracking of fraud attempts, decision outcomes, and false positive rates. Helped leadership shift from static rules to behavior-driven detection models and responsive control logic- Customer Experience Preservation – Integrated downstream signals and cohort-based exception logic to protect good users while stopping fraud. Balanced precision and recall thresholds through test-rollouts, Ops feedback, and CX monitoring to maintain frictionless experiences for high-trust users- Process Scaling & Automation – Automated fraud reporting workflows and implemented KPI alerting systems, reducing Ops dependency by 30% and enabling proactive intervention against emerging fraud vectors.Let’s connect — I’m always open to conversations around fraud lifecycle design, trust and safety, scalable detection programs, and high-risk product environments.

Experience

1. Senior Data Analyst

   Chase

   Feb 2021 — Present · Dallas, TX, US

   Designed and implemented analytical frameworks targeting identity fraud, reducing fraud by 17% through identity scanning strategies. Developed and championed robust A/B testing and decision analytics frameworks to proactively detect and mitigate financial fraud, resulting in a $50M revenue increase by enhancing trust and aligning risk management with business growth. Automated financial risk and abuse reporting processes, saving 20+ man-hours weekly, improving data accuracy, and enabling rapid, informed decision-making in dynamic trust environments. Designed and implemented interactive dashboards using Tableau, reducing manual reporting efforts by 30% and proactively identifying emerging trust and safety risks. Acted as a subject matter expert (SME) on SQL, Tableau, AWS Athena, Snowflake, and SAS, promoting best practices in fraud detection, analytics efficiency, and data security across teams. Optimized cloud-based analytics workflows for fraud detection, achieving a 30% improvement in query performance and reducing execution time by 40%, enabling proactive identification and mitigation of threats to user trust and platform safety.

Education

• Oklahoma State University

  Masters

  2017 — 2019

• Guru Gobind Singh Indraprastha University

  B. Tech

  2009 — 2014

Skills

• Powerpoint
• Tableau
• C
• Programming
• Microsoft Office
• Matlab
• Simulink
• Sas
• Microsoft Sql Server
• C++
• Windows
• Solidworks
• Engineering
• Sql
• Autocad
• Sql Server Reporting Services (Ssrs)
• Electronics
• R