Partner risk management lead

Tiger Analytics is a global leader in AI and analytics, helping Fortune 1000 companies solve their toughest challenges. We offer full-stack AI and analytics services & solutions to empower businesses to achieve real outcomes and value at scale. We are on a mission to push the boundaries of what AI and analytics can do to help enterprises navigate uncertainty and move forward decisively. Our team of 4000+ technologists and consultants are based in the US, Canada, the UK, India, Singapore, and Australia, working closely with clients across CPG, Retail, Insurance, BFS, Manufacturing, Life Sciences, and Healthcare. Many of our team leaders rank in the Top 10 and 40 Under 40 lists, exemplifying our dedication to innovation and excellence.

We are a Great Place to Work-Certified ), recognized by analyst firms such as Forrester, Gartner, HFS, Everest, ISG and others. Financial Times, Economic Times and Analytics India Magazine.

Tiger Analytics is seeking an experienced Quantitative Risk and Model Validation Lead Analyst to join our Banking and Financial Services practice. This position will be part of the broader Model Risk and Validation team , contributing to the design and validation of complex quantitative and mathematical models used across market risk, counterparty credit risk, and credit portfolio risk assessment.

You will be at the intersection of quantitative research and real-world applications, engaging with Finance, Treasury, and Business stakeholders to build, validate, and deploy models that support economic capital, risk measurement, pricing, and performance analytics. The role also offers a strong leadership component in mentoring junior analysts and overseeing model governance and compliance with regulatory frameworks.

As part of larger Financial Services practice, you may getto work on a broadrange of business-critical problems across various work streams. You will be engaging with clients and client partnersto understand theirbusiness context, and work witha team of data scientists and engineers.

Design and validate advanced mathematical and statistical models used to evaluate economic and capital markets, including models for risk-neutral pricing, counterparty credit risk, and sector/industry risk.

# Develop and validate macroeconomic quantitative models that forecast fundamental credit risk metrics such as default rates, charge-offs, severity, prepayments, and balance growth.

# Build numerical simulation models for credit risk valuation and pricing of wholesale, retail, and structured credit exposures.

# Translate quantitative research into high-impact business tools and insights for performance measurement, risk-adjusted pricing, and capital allocation.

# Support model development and validation aligned with Basel, FDIC, and Federal Reserve regulatory frameworks.

# Engage stakeholders across Finance and Risk functions to ensure proper integration and utilization of economic capital models.

# Lead or contribute to documentation, compliance, and internal/external audit requirements.

# Mentor and guide junior team members and review the quality of modeling deliverables.

10+ years of experience in quantitative modeling, financial risk analytics, or model validation in commercial banking or major financial institutions.

# Strong foundation in stochastic processes, time series modeling, portfolio theory, and option valuation .

# Deep understanding of mathematical finance theories and their applications in credit risk and market risk.

# Experience in designing models aligned with regulatory frameworks (Basel, CCAR, FDIC, etc.).

# Proficient in using statistical and mathematical software tools, and in working with relational databases .

Desired Experience:

# Expertise in quantitative risk modeling (credit, market, counterparty).

# Prior experience working with structured products and sector/industry risk assessment .

# Ability to translate quantitative models into value-added business tools for risk management and capital planning.

# Familiarity with Economic Capital models and Risk-Adjusted Return on Capital (RAROC) frameworks.

Experience with regulatory models under IRB, IFRS9, CECL, or CCAR .

# Hands-on model development using Python, PySpark, or SAS .

# Experience in credit risk strategy , including CLI, policy analytics, or scorecard development.

# Exposure to model risk governance and working with internal/external audit or regulatory reviews.

Latest Technology: You will get to work on the most advanced technologies like machine learning and artificial intelligence.

Global Exposure: We work for leading global brands. Learning & Development: We partner with a host of the biggest learning platforms. There is no pressure on you to be a master of everything. Here, you'll work with people with a collective passion to explore the limitless potential of data to solve complex problems.

Additional Benefits: Health insurance (self & family), virtual wellness platform, fun, and knowledge communities.

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