Job Title: Fraud Risk Strategy

Location: Bangalore, Hyderabad and Gurugram

Experience: 3 to 12 years

About Straive:

Straive is a trusted leader in building and operationalizing enterprise data and AI solutions for top global brands and corporations. Our key differentiators include extensive domain expertise across multiple industry verticals, coupled with cutting-edge data analytics and AI capabilities that have consistently driven measurable ROI for our clients. With a global footprint spanning 30+ countries, Straive serves hundreds of clients, supported by a team of 18,000+ seasoned professionals in data, analytics, AI, and operations. Our offices are strategically located across India, the Philippines, the USA, Nicaragua, Vietnam, the UK, Canada, and Singapore, where our headquarters are based.

Company website - https://www.straive.com/about-us/

LinkedIn Page - https://www.linkedin.com/company/straive_/about/

Job Role: Manager / Lead - Fraud Risk Strategy Years of Experience: 3 to 12 Years

Job Summary:

We are seeking a highly analytical and strategic Fraud Risk Manager/Lead to join our team. In this pivotal role, you will be responsible for designing, implementing, and optimizing fraud strategies for a leading global payments ecosystem.

The ideal candidate will bring strong technical expertise in SQL and Python, coupled with a deep understanding of the payment fraud industry. You will play a critical role in managing fraud losses across Consumer-to-Consumer (C2C) and Consumer-to-Business (C2B) payment flows, while simultaneously improving payment authorization rates and ensuring a frictionless customer experience.

Key Responsibilities:

Domain Expertise: Proven experience in the Payments Industry, specifically dealing with Transactional Fraud, Digital Wallets, Payment Gateways, and E-commerce fraud
Fraud Strategy & Mitigation: Design, implement, and manage robust fraud prevention strategies for C2C (peer-to-peer) and C2B (merchant checkout) payment products, as well as Debit Card portfolios (covering both Card Present and Card Not Present transactions).
Authorization Optimization: Analyze transaction data to improve payment authorization rates across various checkout flows (both branded and unbranded/guest checkouts) while keeping fraud losses within risk appetite.
Customer Experience (CX): Balance aggressive fraud mitigation with user experience by minimizing false positives (false declines) and reducing unnecessary friction for legitimate customers.
Data-Driven Investigation: Investigate suspicious transaction patterns, account takeovers (ATO), and payment anomalies to determine root causes and develop proactive statistical models/rules.
System & Rule Development: Design and deploy fraud rules within decision engines and workflow systems. Build comprehensive monitoring reports to track the performance of fraud strategies.

Required Qualifications:

Bachelor's or Master's degree in Finance, Economics, Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field.
3 to 6 years of hands-on experience in fraud strategy, specifically within Fintech, Digital Payments, E-commerce, or Payment Gateways.
Demonstrated experience in designing and implementing fraud rules using transactional, behavioral, and third-party data.
Strong proficiency in:
SQL: Advanced querying, joins, aggregations, and performance tuning for massive transactional datasets.
Python: Data manipulation (Pandas, NumPy), exploratory data analysis, and basic modeling; ability to productionize or hand over code to engineering teams.
Strong analytical and problem-solving skills with the ability to translate data insights into actionable strategies that directly impact the bottom line

Fraud Specialist