P2 Associate Manager - RiskOps

PayU; Gurugram District; On-site; INR 600,000 - 900,000; Full time

Benefits offered by this job

Training courses

Inclusive environment

Global scale

Competitive compensation

Job summary

PayU in Gurgaon is seeking a skilled Risk & Fraud Data Analyst to deliver data analytics support and actionable insights. The role focuses on building automated dashboards and reporting using Python and SQL, enabling informed decisions within fraud risk management.

The ideal candidate will navigate complex data, ensure data quality, and collaborate with global teams to optimize risk controls and operational efficiency.

Qualifications

• Experience in data analytics and reporting using SQL and Python.
• Strong knowledge of Excel for data manipulation.
• Ability to deliver dashboards and metrics to stakeholders.

Responsibilities

• Serve as a central hub for data analytics to inform risk decisions in the Fraud Risk Management team.
• Develop dashboards, metrics, and automated reports using Python and SQL.
• Interpret complex datasets and identify trends to mitigate fraud.
• Monitor KPIs and deliver ongoing data-driven insights to business stakeholders.
• Collaborate with cross-functional teams in a fast-paced, global environment.

Skills

Python

SQL

Excel

Tools

Python

SQL

Excel

Job description

About us:

At PayU, we are a global fintech investor and our vision is to build a world without financial borders where everyone can prosper. We give people in high growth markets the financial services and products they need to thrive. Our expertise in 18+ high-growth markets enables us to extend the reach of financial services. This drives everything we do, from investing in technology entrepreneurs to offering credit to underserved individuals, to helping merchants buy, sell, and operate online. Being part of Prosus, one of the largest technology investors in the world, gives us the presence and expertise to make a real impact. Find out more at www.payu.in

Our Commitment to Building A Diverse and Inclusive Workforce

As a global and multi-cultural organization with varied ethnicities thriving across locations, we realize that our responsibility towards fulfilling the D&I commitment is huge. Therefore, we continuously strive to create a diverse, inclusive, and safe environment, for all our people, communities, and customers. Our leaders are committed to create an inclusive work culture which enables transparency, flexibility, and unbiased attention to every PayUneer so they can succeed, irrespective of gender, color, or personal faith. An environment where every person feels they belong, that they are listened to, and where they are empowered to speak up. At PayU we have zero tolerance towards any form of prejudice whether a specific race, ethnicity, or of persons with disabilities, or the LGBTQ communities.

About the Team

We are the Fraud Risk Management team, operating as a key function within the Risk Operations Vertical of the broader Risk Organisation. Our vertical serves as the operational backbone of the Risk Org, responsible for translating risk strategies into real-time execution, monitoring, and measurable outcomes. Our team's core mandate is the identification, assessment, and mitigation of fraud risks — with a specialised focus on cross-border transactions, where multi-regional complexity creates a constantly evolving threat landscape. We are a highly skilled and dedicated group of professionals who design and deploy advanced rule-based frameworks and logic systems capable of detecting anomalies, flagging suspicious patterns, and identifying irregular consumer behaviour across virtually any transactional parameter. Our rule-building capabilities allow us to rapidly respond to emerging fraud trends, continuously optimise detection models, and strike the right balance between effective fraud prevention and a seamless customer experience. In doing so, we serve as a critical line of defence within the organisation — contributing frontline intelligence and data-driven insights that shape risk decisions across the entire Risk Org.

About the Role

We are seeking a talented Risk and Fraud Data Analyst to deliver data analytics support and meaningful insights to our team. The ideal candidate will be comfortable navigating complex datasets and capable of building robust frameworks to automate dashboards, metrics, and reporting using Python and SQL.

Responsibilities

• Serve as a central hub for intelligence gathering, data analysis, risk mitigation, and fraud assessments that inform decision-making across the Risk portfolio
• Develop actionable roadmaps to continuously improve and automate existing workflows and processes
• Interpret complex datasets and analyse results using advanced analytics, research methodologies, and statistical techniques
• Monitor and evaluate key performance indicators, deliver ongoing reports, and recommend data-driven improvements
• Identify and implement opportunities to enhance data quality and business processes through Python and SQL solutions
• Perform queries across multiple platforms to identify trends and anomalies within transaction data, drawing accurate and timely conclusions

Requirements

• Proficiency in Microsoft Excel and SQL, with a proven ability to deliver high-quality data analysis for internal teams and stakeholders
• Hands-on experience with Python is essential
• Strong attention to detail with a structured, analytical mindset
• Ability to work independently and collaboratively in a fast-paced, international environment

What we offer?

• A positive, get-things-done workplace
• A dynamic, constantly evolving space (change is par for the course – important you are comfortable with this)
• An inclusive environment that ensures we listen to a diverse range of voices when making decisions.
• Ability to learn cutting edge concepts and innovation in an agile start-up environment with a global scale
• Access to 5000+ training courses accessible anytime/anywhere to support your growth and development (Corporate with top learning partners like Harvard, Coursera, Udacity)