Fraud Specialist 1 in India

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Specialist – Regional Customer Success Operations, Services Specialist – Regional Customer Success Operations, Services Overview Services within Mastercard is responsible for acquiring, engaging, and retaining customers by managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience. We provide value-added services and leverage expertise, data-driven insights, and execution. Our Regional Customer Success teams play a crucial role in ensuring our customers achieve their desired outcomes while maximizing the value of our products and services. As advocates for customer experience, this team is accountable for a strong onboarding experience, providing ongoing strategic support, and fostering long-term relationships. They work collaboratively with cross-functional teams to address customer needs, gather feedback on product improvements, develop tailored strategies that enhance customer satisfaction and retention, build customer advocacy to support our B2B marketing campaigns and create leads for value expansion for our Business Development teams. By focusing on proactive engagement and personalized service with our customers, the team is dedicated to driving customer value and contributing to the overall growth of the organization. About the Role Are you passionate ab

Role Overview We are seeking a highly experienced, data-driven Fraud Risk Management professional to lead our fraud detection, investigation, and regulatory compliance frameworks. In this role, you will be responsible for safeguarding our digital payments ecosystem (including UPI, IMPS, Wallets, and Merchant platforms) by engineering advanced risk rules, optimizing machine learning models, and leading high-performing operational teams. You will also act as a primary liaison with key regulatory bodies (RBI, NPCI) and Law Enforcement Agencies (LEAs) to ensure ironclad compliance and proactive risk mitigation. Key Responsibilities 1. Regulatory Compliance & Governance  Implement Circulars: Spearhead the end-to-end implementation of all fraud risk-related circulars and compliance mandates from the RBI, NPCI, and FIU.  Regulatory Confirmation: Own and ensure the timely, accurate submission of critical regulatory implementations on the PCOMP portal.  Stakeholder Liaison: Serve as the primary point of contact for ad-hoc risk inquiries from regulatory bodies and Law Enforcement Agencies (LEA).  Executive Reporting: Prepare and present advanced data analysis and high-level risk reports for Board-level forums, including the Risk Management Committee (RMC). 2. Risk Rule Engineering & Advanced Analytics  Rule Development: Codify, test, and deploy hundreds of high-impact risk rules (velocity, blacklists, compliance) using Python and SQL to counter emerging fraud vectors.  Data Analysis: Query and analyze large-scale transactional and profile data to identify patterns, build automated daily alert reports, and perform Root Cause Analysis (RCA).  ML Model Optimization: Partner cross-functionally with Tech and Data Science teams to refine and optimize Machine Learning/AI-driven risk models to boost detection efficiency and reduce false positives. 3. Fraud Investigations & Operations  Investigations: Lead end-to-end investigations into sophisticated digital payme

Role Purpose: The Machine Learning Engineer IV will play a critical role in advancing Jumio's Fraud team's mission to develop and enhance state-of-the-art solutions for fraud detection for ID verification purposes. This role is essential for ensuring the highest standards of security and user verification through the application of advanced machine learning and deep learning techniques, ultimately contributing to Jumio's leadership in the online identity verification, eKYC, and AML solutions market Role Value: As a Machine Learning Engineer IV at Jumio, you will have the opportunity to significantly impact the security and user experience of our ID verification solutions. Your expertise in deep learning and computer vision will drive the development of innovative algorithms that keep Jumio at the forefront of the industry. By deploying and maintaining these models in production, you will ensure the robustness and reliability of our solutions, supporting our clients across diverse industries such as Financial Services, Travel, Sharing Economy, Fintech, and Gaming. Your contributions will be pivotal in maintaining Jumio's reputation as the leading provider of online identity verification solutions, helping to meet the growing demand for secure and seamless user verification globally. Example Responsibilities . Develop, maintain, and own key fraudulent CV models of Jumio, which shapes the whole fraud product offering of Jumio. Design and implement machine learning, deep learning, classical CV focused on fraud detection. Research to support the deployment of the advanced algorithms. Deploy models as AWS SageMaker endpoints or directly onto devices. Stay updated with the latest advancements in machine learning, deep learning, and computer vision by engaging with academic papers and attending industry conferences. Work collaboratively with other engineers and product managers in an Agile development environment. Experience and Qualifications Bach

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . Payments Risk Analyst II As a Payments Risk Analyst II on the Risk & Fraud team within the Consumer & Business group, you'll own the identification and mitigation of payments fraud across Coinbase's fiat payment rails, including ACH, wire, and card transactions. This team protects millions of customers and billions in transaction volume from chargebacks, unauthorized deposits, and account takeover schemes. You'll investigate escalated fraud cases, analyze risk patterns across multiple channels, and partner cross-functionally to strengthen detection systems across one of crypto's highest-volume retail platforms. What you'll do: Own end-to-end investigation and resolution of escalated payments fraud cases, including chargebacks, ACH returns, wire disputes, and account takeovers, across phone, messaging, and email channels. Analyze fraud trends and patterns across payment activities, synthesizing data into actionable recommendations that improve detection logic and reduce loss exposure. Handle premium and high-complexity customer cases, including CB1, HNWI, and executive escalations, using judgment to make risk decisions and coordinating with stakeholders to resolve issues. Partner cross-functionally with Product, Data Science, Risk ML, and Engineering to develop and iterate on risk management strategies, rule logic, and fraud prevention processes. Identify work

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

 Manage site security operations in harmony with business objectives and Security Strategy Roadmap at major sites  Protect enterprise wide infrastructure to ensure business continuity, creating a safe environment for all employees and stakeholders and ensuring enhanced security and personal safety of “designated protectees”  Address fraud & misconduct through a well-established framework to prevent, detect, respond, and refine strategies and methodologies.  Identify potential threats and calibration of risks from detailed security risk assessments to eliminate, reduce or mitigate risks.  Responsible for ensuring security and protection of tangible and intangible assets, at the site  Responsible for managing security related automation and infrastructure projects Source: Adani Group | Job ID: 52925

Manage site security operations in harmony with business objectives and Security Strategy Roadmap at major sites  Protect enterprise wide infrastructure to ensure business continuity, creating a safe environment for all employees and stakeholders and ensuring enhanced security and personal safety of “designated protectees”  Address fraud & misconduct through a well-established framework to prevent, detect, respond, and refine strategies and methodologies.  Identify potential threats and calibration of risks from detailed security risk assessments to eliminate, reduce or mitigate risks.  Responsible for ensuring security and protection of tangible and intangible assets, at the site  Responsible for managing security related automation and infrastructure projects Source: Adani Group | Job ID: 49655

Manage site security operations in harmony with business objectives and Security Strategy Roadmap at major sites. • Protect enterprise-wide infrastructure to ensure business continuity, creating a safe environment for all • Employees and stakeholders and ensuring enhanced security and personal safety of “designated protected” • Address fraud & misconduct through a well-established framework to prevent, detect, respond, and refine strategies and methodologies. • Identify potential threats and calibration of risks from detailed security risk assessments to eliminate, reduce or mitigate risks. • Responsible for ensuring security and protection of tangible and intangible assets, at the site • Responsible for managing security related automation and infrastructure projects Source: Adani Group | Job ID: 49667

Manage site security operations in harmony with business objectives and Security Strategy Roadmap at major sites. • Protect enterprise-wide infrastructure to ensure business continuity, creating a safe environment for all • Employees and stakeholders and ensuring enhanced security and personal safety of “designated protected” • Address fraud & misconduct through a well-established framework to prevent, detect, respond, and refine strategies and methodologies. • Identify potential threats and calibration of risks from detailed security risk assessments to eliminate, reduce or mitigate risks. • Responsible for ensuring security and protection of tangible and intangible assets, at the site • Responsible for managing security related automation and infrastructure projects Source: Adani Group | Job ID: 50710

About the Team The Monetization team is a new cross-functional group spanning engineering, product, research, and design. We are building the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to create user-first, privacy-preserving monetization products—including next-generation ads experiences—that strengthen trust, expand economic opportunity, and support OpenAI’s long-term innovation. We believe monetization should deliver clear user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem for developers and businesses. The team operates in a greenfield environment, moving quickly through prototyping, experimentation, and iterative deployment. We partner closely across Product, Design, and Research to bring new capabilities into real-world systems at global scale. About the Role We’re looking for an experienced Software Engineer to build the integrity systems that keep OpenAI’s ads products safe, trustworthy, and resilient to abuse. In this foundational role, you will design infrastructure that detects and prevents harmful, deceptive, fraudulent, or policy-violating ads and advertiser behavior at scale. This role is well suited to an engineer who has built large-scale systems in ads integrity, trust and safety, anti-abuse, fraud, security, risk, or a related domain—and who wants to apply that experience in an ambiguous 0→1 environment. You will work across risk signals, detection and enforcement platforms, review tooling, adversarial resilience, advertiser controls, and integrity measurement. We are hiring engineers who can independently own complex systems, make sound technical tradeoffs, and help define what should be built. You will collaborate with Ads Delivery, Ads ML, Product, Research, Safety, Policy, Privacy, Legal, Security, and operations teams to create a high-integrity ads ecosystem from first principles. This role is based in San Francisco. We offer relocation assistance t

The Zonal Lead - Security-Tx is responsible for managing security operations across the cluster in alignment with business objectives and the Security Strategy Roadmap. This includes safeguarding infrastructure to ensure business continuity, fostering a secure environment for employees and stakeholders, and enhancing the security of designated protected. The role oversees fraud and misconduct prevention through a structured framework for detection, response, and continuous improvement. By conducting detailed security risk assessments, the Security Lead identifies, mitigates, and eliminates potential threats while ensuring the protection of tangible and intangible assets within the cluster. Source: Adani Group | Job ID: 55870

Razorpay is one of India’s leading full-stack financial technology companies, powering the way businesses move, manage, and grow money. Founded in 2014 by Harshil Mathur and Shashank Kumar with a simple vision - to simplify payments for Indian businesses - we’ve since grown into a fintech powerhouse driving India’s digital payment revolution. Razorpay powers millions of businesses with a smarter, scalable stack that goes beyond transactions to help them truly build and grow. From building AI-native agentic payments, to AI-assisted fraud detection and real-time risk intelligence to automated reconciliation, smart payouts, and predictive financial insights, we are embedding intelligence across our stack to make money movement faster, safer, and more efficient. In close collaboration with ecosystem partners - including banks, networks, regulators - we are pioneering industry-first solutions that are shaping the next era of fintech Across India, Singapore and Malaysia, our products span everything from seamless checkouts to payroll automation - powering a fintech ecosystem that’s redefining how money moves across Asia. Today, that ecosystem supports everyone from early-stage startups to some of India’s largest enterprises, enabling them to accept, process, and disburse payments at scale while expanding into new ways of managing money more efficiently. Our scale speaks volumes: Razorpay processes $180+ billion in annualized transactions, powering leading businesses like Airbnb, Facebook, WhatsApp, Airtel, CRED, BookmyShow, Zomato, Swiggy, Lenskart, Mirae Asset Capital markets, Indian Oil, National Pension Scheme - and over 100 of India’s unicorns. With strong roots in India and growing operations in Southeast Asia, we are shaping the next chapter of financial technology across the region. We are backed by global investors including GIC, Peak XV Partners (formerly Sequoia Capital India & SEA), Tiger Global, Ribbit Capital, Matrix Partners, MasterCard, and Salesforce V

Razorpay is one of India’s leading full-stack financial technology companies, powering the way businesses move, manage, and grow money. Founded in 2014 by Harshil Mathur and Shashank Kumar with a simple vision - to simplify payments for Indian businesses - we’ve since grown into a fintech powerhouse driving India’s digital payment revolution. Razorpay powers millions of businesses with a smarter, scalable stack that goes beyond transactions to help them truly build and grow. From building AI-native agentic payments, to AI-assisted fraud detection and real-time risk intelligence to automated reconciliation, smart payouts, and predictive financial insights, we are embedding intelligence across our stack to make money movement faster, safer, and more efficient. In close collaboration with ecosystem partners - including banks, networks, regulators - we are pioneering industry-first solutions that are shaping the next era of fintech Across India, Singapore and Malaysia, our products span everything from seamless checkouts to payroll automation - powering a fintech ecosystem that’s redefining how money moves across Asia. Today, that ecosystem supports everyone from early-stage startups to some of India’s largest enterprises, enabling them to accept, process, and disburse payments at scale while expanding into new ways of managing money more efficiently. Our scale speaks volumes: Razorpay processes $180+ billion in annualized transactions, powering leading businesses like Airbnb, Facebook, WhatsApp, Airtel, CRED, BookmyShow, Zomato, Swiggy, Lenskart, Mirae Asset Capital markets, Indian Oil, National Pension Scheme - and over 100 of India’s unicorns. With strong roots in India and growing operations in Southeast Asia, we are shaping the next chapter of financial technology across the region. We are backed by global investors including GIC, Peak XV Partners (formerly Sequoia Capital India & SEA), Tiger Global, Ribbit Capital, Matrix Partners, MasterCard, and Salesforce V