🤖 15+ AI Agents working for you. Find jobs, score and update resumes, cover letter, interview questions, missing keywords, and lots more.
Cookies & analytics consent
We serve candidates globally, so we only activate Google Tag Manager and other analytics after you opt in. This keeps us aligned with GDPR/UK DPA, ePrivacy, LGPD, and similar rules. Essential features still run without analytics cookies.
Read how we use data in our Privacy Policy and Terms of Service.
🤖 15+ AI Agents working for you. Find jobs, score and update resumes, cover letter, interview questions, missing keywords, and lots more.
Citi • Mumbai, Maharashtra, India
Role & seniority: Senior/experienced data analytics professional in risk management (4+ years in financial services or related fields); post-graduate degree in a quantitative discipline.
Stack/tools: Econometric/empirical forecasting models; data science / machine learning; SAS; Datacube/Essbase; MS Office (Excel, PowerPoint).
Forecast losses and loan loss reserves; interpret drivers and trends to produce meaningful, accurate forecasts.
Analyze model outputs, reconcile data from disparate sources, ensure outputs are rational and well-supported; present findings to manager, stakeholders, and senior management.
Ensure governance, documentation, and control practices; drive process automation for data, forecasting, and reporting; support regulatory reviews and audit initiatives.
Strong quantitative background with post-grad specialization; solid understanding of risk management.
4+ years in financial services, business analytics, or management consulting.
Experience with econometric/empirical forecasting; ability to handle large datasets; proficiency with SAS, Datacube/Essbase, and MS Office.
Knowledge of CCAR/Stress Testing concepts is preferred; ability to develop cross-functional partnerships; analytical thinking and risk identification.
Responsibilities include but are not limited to understanding the key drivers of losses and loan loss reserves, their relative importance and the current trends; apply this knowledge effectively to forecast losses / loan loss reserves meaningfully and accurately; analyze underlying model outputs relative to other business, ensure that the models provide rational and logical output, Reconcile detailed financial data from disparate data sources, be able to present the findings to their manager and various key stake-holders and senior management across the organization; hold meaningful discussions and present to various review and challenge and / or audit teams and assist with regulatory reviews; ensure best in class governance and documentation practices for these functions; drive process efficiencies through automation for the underlying data, forecasting and reporting processes Understands and appreciates diverse backgrounds. Demonstrates strong ethics Develops strong cross-functional relationships within and outside Risk Management Contributes to a positive work environment; shares knowledge and supports diversity 4+ years of work experience in financial services, business analytics or management consulting. Post graduate degree with specialization in a quantitative discipline: Statistics, Mathematics, Economics, Econometrics, Management, Operations Research or Engineering Understanding of risk management. Knowledge of credit card industry and key regulatory activities (CCAR) is a plus. Experience in CCAR / DFAST/Stress Testing is preferred. Strong understanding and hands-on experience with econometric and empirical forecasting models. Experience in data science / machine learning is preferred with ability to handle large datasets. Experience in using analytical packages like SAS, Datacube/Essbase, MS Office (Excel, PowerPoint) Vision and ability to provide innovative solutions to core business practices. Ability to develop partnerships across multiple business and functional areas. Ability and experience to drive changes in order to achieve business targets Displays flexibility to work well with varying personal styles Analytical Thinking, Business Acumen, Constructive Debate, Data Analysis, Escalation Management, Policy and Procedure, Policy and Regulation, Risk Controls and Monitors, Risk Identification and Assessment, Statistics. ------------------------------------------------------ For complementary skills, please see above and/or contact the recruiter. ------------------------------------------------------