Senior Quant, AI & Financial Services Lead

This role is for one of the Weekday's clients

Salary range: Rs 4500000 - Rs 7000000 (ie INR 45-70 LPA)

Experience: 10+ yrs

Location: India

Job Type: full-time

We are seeking an experienced Financial Analytics & AI Practice Lead to drive the delivery of advanced analytics, quantitative finance, risk management, and machine learning solutions for financial services organizations. This is a strategic leadership role requiring a strong blend of domain expertise, quantitative modeling capabilities, AI/ML knowledge, and stakeholder management experience.

The ideal candidate will work closely with senior business leaders, including Chief Risk Officers, Chief Financial Officers, Treasurers, Heads of Markets, and Risk Leaders, to understand complex business challenges and translate them into practical analytical solutions. You will lead multidisciplinary teams of data scientists, machine learning engineers, quantitative analysts, and domain experts to design, build, validate, and deploy high-impact solutions across risk, treasury, portfolio management, markets, and banking functions.

This role offers the opportunity to shape innovative financial analytics frameworks, drive AI adoption within financial services, and influence strategic decision-making through data-driven insights and advanced quantitative techniques.

Requirements

Key Responsibilities

• Lead end-to-end delivery of AI, machine learning, quantitative finance, and financial analytics projects for financial services clients.
• Engage with senior stakeholders to understand business challenges and translate them into analytical frameworks, quantitative models, and technology-driven solutions.
• Design, review, and oversee development of models related to credit risk, market risk, liquidity risk, treasury analytics, portfolio management, forecasting, stress testing, valuation, and Asset & Liability Management (ALM).
• Define data requirements, analytical methodologies, implementation strategies, and delivery roadmaps for complex financial analytics engagements.
• Guide teams in developing machine learning models, statistical models, forecasting frameworks, and quantitative solutions.
• Review model assumptions, methodologies, validation results, governance requirements, and technical documentation to ensure quality and regulatory compliance.
• Drive innovation through the application of AI, machine learning, predictive analytics, and quantitative techniques across financial services use cases.
• Support business development activities, including client presentations, solution proposals, workshops, and technical discussions.
• Collaborate with cross-functional teams to develop scalable and reusable analytics frameworks, accelerators, and industry solutions.
• Provide mentorship and technical leadership to data scientists, quantitative analysts, and junior consulting professionals.
• Ensure successful project execution through effective stakeholder management, delivery governance, and risk mitigation.
• Stay current with evolving industry trends, regulatory developments, and emerging technologies impacting financial services analytics.

What Makes You a Great Fit

• 10–15 years of experience in financial services, banking, consulting, asset management, fintech, risk analytics, or related industries.
• Strong expertise in at least two of the following domains: Quantitative Finance, Risk Management, Asset & Liability Management (ALM), Treasury, Markets, Corporate Banking Analytics, Portfolio Analytics, or Structured Finance.
• Proven experience leading complex analytical and quantitative projects from strategy through implementation.
• Strong understanding of Machine Learning techniques, including regression, classification, clustering, forecasting, time series analysis, and predictive modeling.
• Advanced proficiency in Python for analytics, quantitative modeling, automation, and prototyping.
• Deep understanding of financial risk management concepts, including credit risk, market risk, liquidity risk, stress testing, capital management, and portfolio risk analytics.
• Strong foundation in statistics, econometrics, probability, optimization techniques, and financial mathematics.
• Experience working with model validation, governance frameworks, regulatory expectations, and model risk management practices.
• Knowledge of regulatory frameworks such as Basel, IFRS 9, stress testing, ALM, treasury risk, and related financial regulations.
• Ability to engage confidently with senior executives and business leaders to define problems, shape analytical strategies, and communicate insights effectively.
• Proven track record of leading multidisciplinary teams and managing large-scale analytical engagements.
• Strong communication, presentation, and stakeholder management skills.
• Experience working within banks, consulting firms, asset managers, hedge funds, fintech organizations, or risk technology companies is highly desirable.
• Advanced qualifications such as CFA, FRM, CQF, MSc, or PhD in Finance, Mathematics, Economics, Engineering, Computer Science, Physics, or related disciplines are advantageous.
• Strategic mindset with the ability to bridge business objectives, quantitative methodologies, and technology-driven solutions.