Risk Quantitative Sr Analyst-AVP/VP for FL and TX
Citi, the leading global bank, has approximately 200 million customer accounts and does business in more than 160 countries and jurisdictions. Citi provides consumers, corporations, governments and institutions with a broad range of financial products and services, including consumer banking and credit, corporate and investment banking, securities brokerage, transaction services, and wealth management. Our core activities are safeguarding assets, lending money, making payments and accessing the capital markets on behalf of our clients.
Diversity is a key business imperative and a source of strength at Citi. We serve clients from every walk of life, every background and every origin. Our goal is to have our workforce reflect this same diversity at all levels. Citi has made it a priority to foster a culture where the best people want to work, where individuals are promoted based on merit, where we value and demand respect for others and where opportunities to develop are widely available to all.
About Finance Chief Risk Office
The Finance Chief Risk Office mandates includes: (i) independent risk management oversight over the front line activities of the Finance organization in an integrated and comprehensive manner, (ii) align the stress testing, risk measurement and modeling as well as data, reporting and infrastructure capabilities of Risk Management for loss forecasting, capital planning and reporting.
Finance Chief Risk Office Openings
Finance Chief Risk Office has openings for Assistant Vice Presidents (C12), and Vice Presidents (C13) in Irving, TX and Tampa, FL. Grade level is a function of experience and breadth and depth of knowledge
Locations of openings are indicated next to team name. For completeness, descriptions of all departments that comprise Finance CRO are provided below.
Model Analysis Group (Irving C12/C13; Tampa C12/C13)
The objectives of the Model Analysis Group (MAG) are to drive productivity enhancements and capture synergies in post model development analytics (PMDA), for models developed by QRS Teams. Key to delivering on these objectives is enhancing the documentation, automation, and replicability of PMDA research and activities. While this leads to efficiency, it also facilities the transfer of knowledge amongst MAG Team members allowing them to gain experience across multiple risk stripes thereby enhancing mobility and growth potential within QRS and the larger Risk organization.
With about 180 of QRS's 209 models currently covered by the Model Analysis Group, the remaining models to be transitioned, and more models seeming to come on line every quarter, PMDA is a growing business.
Strategy Office (Irving C13)
The Strategy Office is responsible for ensuring the team meets its goals and objectives via
- Execution and thought-leadership on Strategic Initiatives such as Innovation, location-footprint redesign, work prioritization, and workflow reengineering;
- Management of talent pipeline, working with HR, and other partners to define strategy/goals and execute talent initiatives;
- Clear and effective communication to senior management on goals, significant programs, and analytic topics;
- Setting, managing and monitoring the budgets and expenses process;
- Manage communication channels to ensure QRS leadership vision and decisions are clearly socialized within the QRS employee population;
- Provision of PMO support to the Economic Forecasting Team and
- Cover "ad hoc" requests that arise for the head of QRS pertaining to management and strategy areas.
Counterparty Risk Analytics (CRA) (C12 Tampa)
The CRA team is responsible for developing and maintaining the methodologies to calculate counterparty credit risk exposures of OTC derivatives, exchanged-traded derivatives, security financing transactions, and margined loans. The models are used for advanced Basel regulatory capital calculations, CCAR/Internal Capital Adequacy Assessment Process (ICAAP) estimations, and internal risk management measures (PFE/EPE).
Additionally, the team provides live-deal analysis to business and risk management by calculating credit exposure factors at trade and portfolio levels, estimating allowable collateral levels, and determining initial margin requirements. The team also conducts impact analysis for capital optimization initiatives and new regulatory rules related to counterparty risk, and ensures models and data logics are implemented correctly in credit risk systems.
Risk Capital Analytics (RCA) (C12 Irving &Tampa; C13 Tampa)
The RCA team is responsible for defining the overall framework and principles of Risk Capital (RC) across market risk, wholesale and retail credit risk, pension risk, and ALM risk. RC is a firm-wide metric to measure economic capital usage at the consolidated group as well at the detailed business unit level. It is reported to regulators and the Board as a key capital adequacy metric for Citi and its major legal entities. RC is also used extensively to set risk limits and to assess the risk-adjusted profitability of large transactions.
Credit and Obligor Risk Analytics (CORA) (Irving C12/C13; Tampa C12/C13)
The CORA team is responsible for covering enterprise-wide model development for wholesale and retail credit risk. CORA models are used to estimate advanced Basel III regulatory capital parameters and Global Systemic Stress Testing.
CORA models produce the CCAR and ICAAP estimations. Other wholesale models cover loan loss reserves (IFRS 9/ CECL), cost of credit, obligor risk ratings (debt rating models), liquidity stress testing, RWA stress testing, and market-based default and downgrade risk models. The team is responsible for the life cycle development of all Citi’s wholesale probability of default models used to rate small to mid-size or mid-market enterprises and large corporates as well as commercial banks on a global basis. These models are used by approximately 3,000 risk managers throughout Citi who rate 50,000 obligors with $1 trillion in exposure in the wholesale portfolio.
CORA is also responsible for approval of all risk rating policies and processes for wholesale portfolios.
Enterprise Stress Testing (Irving C12/C13; Tampa C12/C13)
The Enterprise Stress Testing team is responsible for enhancing Citi’s internal Stress Testing (e.g. GSST) and infrastructure. Firm wide stress testing methodologies are widely used in Citi’s identification and measurement of tail risks to assess potential vulnerabilities and capital adequacy. These are foundational elements used in the firm’s risk-return metrics, Board and regulatory reporting, and limit setting frameworks at both Group/CBNA level and certain business/geographic segments.
The Enterprise Stress Testing team is responsible for defining the overall framework and principles of key non-CCAR stress testing methodologies (e.g. GSST and conditional stress loss) and measurement/monitoring of systemic risks. The team is also responsible for developing risk management applications based on these methodologies (e.g. centralized ICAAP tools, firm wide internal stress testing, concentration risk, countercyclical limit setting) to quantify key tail risks and ensure consistent and accurate risk measurement across the firm
Economic Forecasting Team (Irving C12)
Economic Forecasting Team is responsible for forecasting firm wide macroeconomic and financial variables that are critical inputs to a variety of corporate stress tests, loan loss reserves and financial planning model. These includes, CCAR, MCST, Mid-Year-Forecast for Corporate Planning, Annual Corporate Operating Plan, ICAAP, forward looking indicator (FLI) forecast for IFRS, CECL and Global Systemic Stress Tests (GSST's). The team heavily relies on advanced time series and macro econometrics modeling of global economies, with a focus on macro-monetary-financial interlinkages.
- Solid programming skills, with experience of statistical/data analysis techniques and numerical implementations and some familiarity of modern software development tools, is required. Specific experience in SAS, Python, R, using statistical packages and regression models, C/C++, UNIX, databases, and version control systems is particularly advantageous
- Knowledge/experience with Machine Learning Tools and Frameworks (scikit-learn, Teano, Keras, etc) is a plus
- Excellent written and verbal communication skills, with ability to synthesize complex technical information and explain it clearly, is required
- For more senior applicants, actual hands-on experience of quantitative financial modelling (research, development, implementation) and maintaining detailed technical documentation for models, model validation, projects plans and processes, is highly advantageous
- 3+ years of relevant experience
- Minimum of Master’s degree in a quantitative field (physics, mathematics, computer science, etc.) with relevant experience
- Fewer years of relevant experience will be considered for candidates with higher academic qualifications and/or certifications such as a PhD, a second Master’s degree, CPA or CFA
- Proficient in Microsoft Office with an emphasis on MS Excel
- Consistently demonstrates clear and concise written and verbal communication skills
- Self-motivated and detail oriented
- Demonstrated project management and organizational skills and capability to handle multiple projects at one time .
- Practical experience using SAS or similar statistical coding software to build and test prediction models. comfortable interfacing with business clients. proficiency handling very large data sets.
- Experience in a quantitative role in risk management at a financial institution with experience in either model development or validation.
- Good knowledge and understanding of a variety of model development and validation testing techniques covering risk models.
- Excellent programming skill and data analysis capability are essential, especially in C/C++, python, shell scripts, VBA and basic database skills in either Oracle or Sybase.
- Experience of one or more of the following is an advantage but not essential: derivative pricing and exotic products; risk management practices and procedures; numerical methods; Monte Carlo simulations; statistical hypotheses testing.
- Good communication skill is required. Be organized, disciplined and detail oriented.
- Keen interest in banking and finance, especially in the field of Risk Management.
- Highly motivated, with ability to work both independently and collaboratively
- Logical and thoughtful approach to work, with ability to perform well under pressure to meet tight deadlines
- Giving careful attention to detail, with capability to deliver high quality results
- Potential to build trusted relationships confidently at all levels
What’s on offer?
The successful candidate will have the opportunity to work on a wide range of cutting-edge analytical problems, relevant for senior management decision making (CRO, CFO, Board) and regulatory management. The candidate will interact with highly-experienced quantitative analysts and risk management professionals across multiple risk types and geographies, and in so doing gain an expansive view of the firm and its business lines. This is an opportunity to grow within a highly-quantitative team in a challenging area of the financial industry working for one of the world’s leading companies.
Job Family Group:Risk Management
Job Family:Risk Analytics, Modeling, and Validation
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Qualified applicants will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
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