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Risk Analyst

Fin

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This role on the market

1,342 open risk roles across 172 companies are on ApplySarthi right now, most of them in Bengaluru (107), Delhi NCR (60), Mumbai (36).

What risk roles keep asking for: SQL (12%) — counted across their open postings here.

CRM jobs · Machine learning jobs · Python jobs · R jobs

Fin has 123 open roles listed here.

Counted across 14 company job boards, updated as roles open and close.

Preparing for this interview

Interviews for risk roles keep coming back to SQL. Practise those questions before you sit with Fin.

Questions you are likely to be asked

  1. Why do you want to join Fin?
  2. What is your experience with Machine learning? Tell me one thing you learned the hard way.
  3. Explain a join or a window function you have used, and why you needed it.
  4. How would you explain a surprising number to a manager who does not believe it?
  5. Tell me about an analysis that changed a decision. What did you find?

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About Fin Fin is a next-generation payments platform built for high-value, global, and instant transactions. We are a Series A-stage company backed by Sequoia, Circle, and other notable investors. Powered by stablecoins, Fin enables users and businesses to move millions of dollars in seconds - whether to other Fin users, directly into bank accounts, or across crypto rails. By combining the speed of crypto with the reliability and trust of traditional finance, Fin reimagines how money moves worldwide. If banks and payment products were reinvented today, they would look like Fin. Role Overview We are hiring our first Fraud/Risk Analyst to join our Risk & Compliance team . This role will focus on identifying, analyzing, and mitigating risks associated with digital asset transactions – including ACH fraud and compliance with applicable regulations like the Patriot Act and Bank Secrecy Act. This is a critical position, reporting directly to the CEO, and will require a combination of technical, analytical, and regulatory expertise to build a robust fraud detection and risk assessment framework from the ground up. Key Responsibilities Develop and implement a comprehensive risk management strategy tailored to the evolving digital asset landscape. Take action to resolve automatically flagged transactions and individuals File suspicious activity reports as required Monitor and analyze transaction data to detect potential fraud, suspicious activities, and emerging risk trends. Utilize advanced data analysis techniques and fraud detection tools to identify anomalies and potential security threats. Create and maintain risk assessment models to evaluate the financial and reputational impact of potential fraud incidents. Partner with the engineering team to design and implement fraud detection systems, leveraging machine learning and predictive analytics. Ensure alignment with regulatory requirements, including AML, KYC, and digital asset regulations. Draft detailed reports and dashboards on risk findings, fraud incidents, and risk mitigation strategies for senior leadership and stakeholders. Lead cross-functional risk assessments for new product launches, ensuring security and fraud prevention measures are integrated into product design. Stay abreast of emerging risks in the digital asset space, including regulatory changes and new fraud tactics. Develop incident response plans for fraud detection and participate in incident response drills to assess and enhance our risk management framework. Qualifications Bachelor's degree in Finance, Economics, Computer Science, Data Science, or related field. 5+ years of experience in fraud analysis, risk management, or financial crime prevention, ideally within fintech, digital assets, or blockchain environments. Demonstrated experience with fraud detection systems, transaction monitoring tools, and data analysis platforms (SQL, Python, R). Strong knowledge of digital asset platforms, blockchain technology, and stablecoin ecosystems. Experience with regulatory compliance, particularly regarding AML, KYC, and financial crime prevention. Exceptional analytical and problem-solving skills with a data-driven approach to decision-making. Strong written and verbal communication skills, with the ability to clearly articulate complex risk findings to non-technical stakeholders. Preferred Qualifications Certifications such as Certified Fraud Examiner (CFE), Certified Risk Manager (CRM), or CAMS. Experience with machine learning models for fraud detection and predictive analytics. Familiarity with incident response protocols and risk mitigation frameworks in financial services. Prior experience in a fast-paced startup or scaling fintech environment.

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Listed on ashby · posted 2025-12-03. ApplySarthi collects openings and links to application pages; the role is advertised by Fin, not by us.