TL-Maps

Job Summary

This role involves managing end to end fraud prevention and monitoring initiatives with experience in SQL + Python for Data Analysis within the maps and location intelligence domain for an international organization. The professional will design and optimize controls analyze complex behavioral patterns and coordinate with cross functional partners to safeguard platform integrity. The position is based in office with rotational shifts and focuses on delivering secure and reliable mapping experiences for global users.

Requirements & Responsibilities

           A Minimum of 4+ Years - Experience in Fraud detection across any of these domains

           Experience in SQL + Python for Data Analysis 

           Solve complex, open-ended abuse problems in UGC Reviews 

           Critical thinking -ability to conduct independent investigative work 

           Creative problem-solving skills

           Investigative skills - Analysing data patterns, and assessing risks

           Delivering complex analysis projects and working on open ended problems

           Experience with fraud and abuse dynamics in online platforms. ever-changing environment.

           Experience in policy/program management, User and merchant experience, business strategy, or related fields

           Knowledge of content moderation, policy enforcement, customer support, and/or policy creation

           Knowledge of AI/ML, Gen AI.

           Drive comprehensive fraud monitoring activities on maps-based platforms by continuously analysing transactional and behavioural patterns to identify emerging threats and reduce loss for the organization and its customers.

           Leverage data analysis techniques on location-based signals to detect anomalies and suspicious activities while ensuring that mapping services remain reliable and trusted across diverse regions and user segments.

           Coordinate with product managers and engineering teams to refine fraud detection rules for map related features so that legitimate user activity is preserved while fraudulent behaviour is accurately captured and acted upon.

           Implement scalable workflows for case review and incident handling in the fraud prevention area ensuring that alerts are triaged efficiently and that response times support a secure and seamless user experience.

           Document fraud trends and map related attack scenarios in clear operational playbooks enabling consistent handling of incidents and ongoing improvement of preventive and detective controls.

           Monitor performance of fraud detection models and rule sets on maps data by reviewing precision metrics and false positive rates then recommending targeted adjustments that balance protection with usability.

           Collaborate with compliance and risk stakeholders to align fraud monitoring practices in the maps environment with internal policies and external regulatory expectations relevant to digital platforms.