Elevate Your Impact Through Innovation and Learning Evalueserve is a global leader in delivering innovative and sustainable solutions to a diverse range of clients, including over 30% of Fortune 500 companies. With a presence in more than 45 countries across five continents, we excel in leveraging state-of-the-art technology, artificial intelligence, and unparalleled subject matter expertise to elevate our clients' business impact and strategic decision-making. Our global network also extends to emerging markets like Colombia, the Middle East, and the rest of Asia-Pacific. Recognized by Great Place to Work ® in India, Chile, Romania, the US, and the UK in 2022, we offer a dynamic, growth-oriented, and meritocracy-based culture that prioritizes continuous learning and skill development, work-life balance, and equal opportunity for all.
About Risk and Quant Solutions (RQS)
Risk and Quant is one of the fastest growing practices at Evalueserve. As an RQS team member, you will address some of the world’s largest financial needs with technology proven solutions. You would solve these banking challenges and improve decision making with award winning solutions.
A senior risk‑focused SME to lead AI/ML governance for the Risk & Quant function, ensuring model integrity, regulatory compliance, and safe deployment of AI across trading, pricing, credit, and operational use cases.
Design, maintain, and operationalize AI governance frameworks, policies, standards, and playbooks aligned with global regulations such as the EU AI Act and GDPR.
Lead quantitative and qualitative model risk assessments for ML/AI models, covering bias, fairness, explainability, calibration, robustness, hallucination, and safety reviews.
Design and implement comprehensive testing modules covering AI behaviour testing, prompt testing, adversarial and robustness testing, performance back‑testing, stress scenarios, and data‑quality validation with automated test suites and pass/fail criteria.
Define risk‑tiered control gates, documented approval workflows, evidence requirements, and immutable audit trails for model development, validation, deployment, and decommissioning.
Maintain a regulatory watch on data protection, sectoral rules, and emerging AI laws; translate requirements into concrete controls, contractual clauses, and validation criteria
Partner with quants, data engineering, production ops, legal, compliance, and business stakeholders to embed governance into the model lifecycle and act as an escalation point for high‑risk decisions.
Build training programs, playbooks, templates, and governance tooling (model registries, checklists, dashboards) to scale responsible AI practices across the organization.
Bachelor’s degree or higher in finance, mathematics, statistics, engineering, or a related field.
~ Certifications such as RAI, FRM, CQF, CFA is a plus
~5–10+ years in model risk, quantitative model validation, AI/ML governance, or related roles within financial services, with demonstrable experience across quant models and production ML systems.
~ Strong understanding of ML algorithms, statistical validation, backtesting, explainability techniques, and model lifecycle management.
~ Practical knowledge of model risk guidance, data protection laws, the EU AI Act implications, and relevant industry standards.
~ Understanding financial instruments/derivatives across all silos i. FX, interest rate, commodity, credit derivative.
~ Proficient in programming languages, such as Python or C++ with a good understanding of object-oriented programming concepts
~ Project management and leadership qualities
~ Excellent communication and stakeholder management skills.
~ Familiarity with model risk guidance and data protection requirements.
As part of the Background Verification Process, we verify your employment, education, and personal details.
