Citi Group AVP Model/Anlys/Valid Sr Analyst - C12 Hybrid 

United States, Delaware 

83154320

• The Model/Anlys/Valid Sr Analyst is a seasoned professional role. Applies in-depth disciplinary knowledge, contributing to the development of new techniques and the improvement of processes and work-flow for the area or function. Integrates subject matter and industry expertise within a defined area. Requires in-depth understanding of how areas collectively integrate within the sub-function as well as coordinate and contribute to the objectives of the function and overall business. Evaluates moderately complex and variable issues with substantial potential impact, where development of an approach/taking of an action involves weighing various alternatives and balancing potentially conflicting situations using multiple sources of information. Requires good analytical skills in order to filter, prioritize and validate potentially complex and dynamic material from multiple sources. Strong communication and diplomacy skills are required. Regularly assumes informal/formal leadership role within teams. Involved in coaching and training of new recruits
• Significant impact in terms of project size, geography, etc. by influencing decisions through advice, counsel and/or facilitating services to others in area of specialization. Work and performance of all teams in the area are directly affected by the performance of the individual.

Responsibilities:

• Bachelor’s/University degree or equivalent experience
• Qualifications:Education:
  • Develop Machine learning credit risk models, validation, deployment efforts, and overall model inventory management.
  • Leverages big data to develop innovative deployable solutions.
  • Manages credit life cycle end-to-end risk strategy ongoing performance evaluation, annual model review, and MRM (Model Risk Management) required documentation preparation and obtaining approvals.
  • Develops, enhances, and validates the methods of measuring and analyzing risk, for all risk types including market, credit and operational. Also, may develop, validate and strategize uses of scoring models and scoring model related policies.
  • Conducts statistical analysis for risk related projects and data modeling/validation.
  • Applies quantitative and qualitative data analysis methods including SAS programming, Structured Query Language (SQL) to extract, transform and analyze data and Visual Basic programming language.
  • Prepares statistical and non-statistical data exploration, validate data, identify data quality issues.
  • Conducts data analysis, data mining, read and create formal statistical documentation, reports and work with Technology to address issues.
  • Analyzes and interprets data reports, make recommendations addressing business needs.
  • Uses Predictive modeling methods, Optimizing monitoring systems, document optimization solutions, and present results to non-technical audiences; create formal documentation using statistical vocabulary.
  • Generates statistical models to improve methods of obtaining and evaluating quantitative and qualitative data and identify relationships and trends in data and factors affecting research results.
  • Validates assumptions; escalate identified risks and sensitive areas in methodology and process.
  • Automates data extraction and data preprocessing tasks, perform ad hoc data analyses, design and maintain complex data manipulation processes, and provide documentation and presentations.
  • Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency.
  • 5-8 years experience
  • Proficient in Python and SAS
  • 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

Responsibilities:

• Develop Machine learning credit risk models, validation, deployment efforts, and overall model inventory management.
• Leverages big data to develop innovative deployable solutions.
• Manages credit life cycle end-to-end risk strategy ongoing performance evaluation, annual model review, and MRM (Model Risk Management) required documentation preparation and obtaining approvals.
• Conducts analysis and packages it into detailed technical documentation report for validation purposes sufficient to meet regulatory guidelines and exceed industry standards.
• Produces analytics and Tableau reporting used to manage model inventory trend.
• Leverage a variety of technologies such as SAS, Python, Spark, AWS and more to extract the value out of the data.
• Deliver on all phases of development, from design through training, testing, validation, and implementation.
• Work with Technology, Risk policy and Governance teams to deliver decision risk models in the market
• Practice your presentation and articulation skills to translate the complexity of your work to all types of audience.

Qualifications

• 3+ years’ experience in Machine Learning risk model in financial institution or PhD degree in Statistics, Data Science, or equivalent experience.
• Sound knowledge of statistical modeling concepts and industry best practices; experience with econometric and statistical modeling or risk models
• Excellent quantitative and analytic skills; ability to derive patterns, trends, and insights
• Experience with analytical or data manipulation tools (e.g. SAS, SQL, R, Python, Spark) Proficient with MS Office suite
• Consistently demonstrates clear and concise written and verbal communication skills
• Self-motivated and detail oriented
• Experience working in Big data environments; Intellectual curiosity to stay abreast of technological advances

Education:

• Bachelor’s/University degree in Statistics, Mathematics, Data Science or equivalent experience. Master’s/PhD degree is a plus

Anticipated Posting Close Date:

View the " " poster. View the .

View the .

View the