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Financial Crimes Specialist

3 weeks ago

Gulbarga, Karnataka, India beBeeRiskAssessment Full time ₹ 18,75,000 - ₹ 25,12,500

Job Role: Senior Fraud Risk Modeler

A key responsibility of this role is designing and developing models to detect and prevent fraud across various financial products.

  • Model Development & Validation: Develop, implement, and validate fraud detection models using advanced statistical techniques for credit card products. This includes creating predictive models to identify high-risk transactions and develop strategies to mitigate potential losses.
  • Data Analysis & Interpretation: Analyze large-scale transactional data to identify patterns and trends indicative of fraudulent activity. Assess model performance and provide insights on areas for improvement.
  • Risk Assessment & Monitoring: Continuously evaluate existing fraud controls, monitor fraud trends, and quantify exposure to evolving threats. Identify opportunities to enhance risk management strategies and ensure compliance with regulatory requirements.
  • Communication & Collaboration: Effectively present analytical findings to stakeholders, including technical and non-technical teams. Foster a collaborative environment and facilitate knowledge sharing to drive business growth.
  • Technical Skills: Possess strong proficiency in Python, SQL, and data science tools. Utilize machine learning and statistical techniques to develop and maintain robust fraud risk models.
  • Domain Expertise: Demonstrate a deep understanding of the credit card product domain, including industry trends, regulations, and market dynamics.
  • Leadership & Teamwork: Provide leadership on analytics initiatives and collaborate with cross-functional teams to achieve business objectives.

Required Qualifications:

  • Bachelor's or Master's degree in a quantitative discipline such as Statistics, Mathematics, or Computer Science.
  • At least 6 years of experience in developing and maintaining fraud risk models.
  • Proven experience in fraud analytics and modelling.
  • Strong programming skills in Python, SQL, or R.
  • Proficiency in machine learning and statistical techniques.
  • Solid understanding of linear regression and XGBoost.
  • Excellent communication and stakeholder management skills.