Risk and Fraud Analytics Manager

Tredence is a global data science and AI solutions provider specializing in providing data-driven solutions to organizations and focused on solving the last-mile problem in AI. Headquartered in San Jose, with offices in Foster City, Chicago, London, Toronto, and Bangalore, Pune, Gurgaon, Chennai, Kolkata.

Tredence is 2200-plus employees strong and caters to the largest companies in retail, CPG, hi-tech, telecom, healthcare, travel, banking, and industrials as clients.

Recognized as one of the fastest-growing private companies in the country for the 7th consecutive year, as per the Inc. 5000, Tredence has twice been named a 'Market Leader' in The Forrester Wave™ : Customer Analytics Service Providers. In its 10th year, Tredence closed a USD 175 million Series B funding last year, which will help us build on growth momentum, strengthen vertical capabilities, and reach a broader customer base.

Tredence has been certified twice as a Great Place to Work (GPTW) that values its employees and creates a positive work culture by providing opportunities for professional development and promoting work-life balance. As a premier destination for high-quality data science and analytics talent, Tredence has strong programs for training, engagement, recognition, and development.

We are seeking a skilled Digital Analytics and Optimization Specialist to drive deep insights into user interactions, website performance, and e-commerce sales. The ideal candidate will leverage clickstream data, Google Analytics, funnel analytics, and ad performance metrics to identify user behavior patterns and conversion blockers. They will implement data-driven personalization strategies to optimize user experience and maximize ROI from search ads.

Key Responsibilities :

• Lead and mentor a team of analysts and data scientists delivering risk and fraud analytics solutions for global retail clients
• Develop and deploy analytical frameworks for fraud detection, anomaly identification, transaction risk scoring, and payment integrity
• Monitor current trends in Fraud landscape, suggest preventive & corrective measures
• Advise clients on a wide range of Fraud Management / Analytics initiatives.
• Collaborate with product, engineering, and operations teams to translate business risks into measurable data strategies
• Design dashboards and monitoring systems to track suspicious activity and risk KPIs
• Leverage machine learning, statistical modeling, and pattern recognition to proactively detect fraudulent behavior
• Own and manage end-to-end delivery roadmaps and translate business objectives into structured execution plans, with clear milestones, deliverables, and success metrics.
• Communicate insights and recommendations to senior stakeholders, influencing policy and platform controls
• Introduce best practices in program governance — sprint tracking, delivery scorecards, dashboards, and reporting frameworks.

What we are looking for

Good to have