Risk Manager

Moder

Bengaluru

Sur place

INR 2 000 000 - 3 000 000

Plein temps

14 jours+

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Résumé du poste

A leading tech outsourcing firm in Bengaluru is seeking an experienced Senior Quantitative Model Risk Manager. This role involves leading independent model validation and contributing to Model Risk Management governance across various risk models. The ideal candidate will have 10–15 years of experience in financial services with a strong focus on Model Risk Management and validation. Master’s degree in a quantitative discipline and proficiency in Python are essential. The position offers a unique opportunity to influence MRM frameworks and collaborate with cross-functional teams.

Qualifications

  • 10–15 years of experience in financial services focused on Model Risk Management.
  • Demonstrated validation experience with credit risk and mortgage-related models.
  • Hands-on experience with Python for data analysis and validation workflows.

Responsabilités

  • Lead independent model validation for various risk models according to SR 11-7/SS 1/23.
  • Draft and maintain MRM policies, standards, and procedures.
  • Produce high-quality validation reports for management and regulators.

Connaissances

Model Risk Management
Python
Documentation skills
Quantitative risk analysis
Collaboration

Formation

Master’s degree in a quantitative discipline

Outils

SQL

Description du poste

About Us

Moder formerly known as Archwell Operations is a part of Archwell Holdings founded in 2017. We are a tech forward outsourcing company specialising in supporting the US Mortgage, Insurance, and Banking industries. We specialise in end‑to‑end component‑based outsourcing, managing one‑off projects to becoming an extension of the customer service or operations team. Our team is built on industry expertise and provides the traction clients need to grow their company.

Equipped with diverse tools, platforms, solutions, and services we strive to work towards our mission to positively impact the financial health of companies by powering in‑house processes using top talent, workflow best practices, and progressive technology.

Link - https://www.gomoder.com/about-moder

Senior Quantitative Model Risk Manager / Model Validator (10–15 years)

We are seeking an experienced quantitative professional to lead independent model validation and contribute to Model Risk Management (MRM) governance across credit, mortgage, and liquidity risk models. The role combines hands‑on validation per SR 11‑7/SS 1/23, policy/procedure drafting, and close partnership with leadership to support in enterprise MRM governance framework. Exposure to mortgage products (including MSR and whole loans), CECL/CCAR/DFAST, and Python is required; mortgage valuation knowledge and modern ML techniques are strong pluses.

Key Responsibilities
  • Draft, refine, and maintain Model Risk Management (MRM) policies, standards, and procedures; translate regulatory guidance into actionable control requirements and validation/testing protocols.
  • Assist leadership in finalising and operationalising the MRM governance framework (roles/responsibilities, inventories, tiering, lifecycle controls, issue management, periodic monitoring, and reporting).
  • Experience contributing to the drafting of MRM policy/standards/procedures and standing up governance routines (e.g., committees, inventory/tiering, model change/use controls).
  • Lead independent model validation reviews end‑to‑end (planning, testing, documentation, and challenge) for PD, LGD, EAD, prepayment, behavioural/credit loss, liquidity (NII/EVE), and other risk models—ensuring conceptual soundness, process verification, data lineage, performance/monitoring, benchmarking, and outcomes analysis in line with SR 11‑7/SS 1/23.
  • Perform technical testing such as sensitivity/scenario analysis, back‑testing, stability tests, challenger builds/benchmarking, and outcome analysis for regulatory and business‑use models.
  • Review and challenge model documentation—assumptions, limitations, data quality controls, implementation, change management, and use—ensuring audit‑ready evidence and clear traceability.
  • Produce high‑quality validation reports and executive summaries suitable for management committees, Internal Audit, and regulators (CECL, CCAR, DFAST contexts).
  • Partner with credit, treasury/ALM, capital planning, finance, and data/technology teams to close validation findings, improve documentation, and strengthen ongoing performance monitoring.
  • Support model inventory accuracy, issue management tracking, and metrics/KRIs for governance dashboards; help standardise templates, test scripts, and review checklists.
  • Coach/mentor junior validators and contribute to playbooks, workpapers, and automation accelerators to improve consistency and throughput.
Qualifications (Must Have)
  • 10–15 years of total experience in financial services/quantitative risk; substantial recent experience focused on Model Risk Management and independent Model Validation.
  • Demonstrated validation experience aligned to SR 11‑7/SS 1/23 across credit risk (PD, LGD, EAD) and mortgage‑related models; familiarity with liquidity/ALM models (e.g., NII/EVE).
  • Hands‑on programming: Python for data preparation, analysis, testing, and automation of validation work‑papers; working knowledge of SQL (and/or R) is a plus.
  • Strong knowledge of banking and regulatory frameworks relevant to model risk and capital planning: CECL, CCAR, and DFAST.
  • Excellent documentation skills—able to produce clear, complete, and audit‑ready validation reports and governance materials.
  • Ability to influence and collaborate with leadership and cross‑functional teams; strong written and verbal communication skills.
Good to Have
  • Exposure to mortgage valuations (e.g., MSR and whole loan valuation workflows, prepayment model review, benchmarking, and sensitivity analysis).
Education

Master’s degree in a quantitative discipline (Statistics, Mathematics, Econometrics, Engineering, Computer Science, or related). Relevant professional certifications (e.g., FRM/CFA) are a plus.

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