urgent hiring For Head - Risk Analyst

10 - 15 years

20 - 30 Lacs

Posted:3 days ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

Role & responsibilities

We are seeking a strategic and analytical leader to lead the Risk Analytics function for our Affordable housing finance business. The role involves developing and implementing advanced risk models, monitoring portfolio health, driving data-driven risk decisions, and working closely with business, compliance, and technology teams to ensure a robust risk framework. Looking for a dynamic and hands-on professional to lead the Risk Analytics function for our affordable housing finance business. The ideal candidate will bring a strong blend of domain knowledge, analytical rigor, and a practical approach suited to the realities of lending to the informal and low-income segment. This role is critical to ensuring healthy portfolio performance while supporting scalable, data-driven growth.

Preferred candidate profile

  • 1015 years in risk analytics, preferably in housing finance or financial services
  • Proven experience in risk analytics, particularly in retail lending / housing finance/ affordable housing finance
  • Strong problem-solving and communication skills; ability to present insights to non-technical stakeholders
  • Strong understanding of credit risk, portfolio analysis, and regulatory requirements (e.g., NHB, RBI)
  • Proficiency in analytical tools (SAS, R, Python, SQL, Excel, etc.)
  • Hands on experience in ECL/ICAAP/Control Assessments
  • Strategic mindset with hands-on approach to data and analytics
  • Self-starter with a practical approach and ability to operate in a lean and fast-paced environment
  • Knowledge of scorecard development, building rule-engine for low-income segment using ML models, and decision systems
  • Experience in digital lending platforms or fintech environment, Understanding of field-level credit operations and customer profiles in affordable housing
  • Familiarity with NHB guidelines and risk-based pricing approaches and Indian Accounting Standard / Expected Credit Loss modelling

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