AVP, Model/Anlys/Valid Sr Analyst - C12 (Hybrid)

• 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

Machine Learning Model Developer and Credit Manager is a strategic professional who stays abreast of developments within own field and contributes to directional strategy by considering their application in own job and the business. Recognized technical authority for an area within the business. Requires basic commercial awareness. There are typically multiple people within the business that provide the same level of subject matter expertise. Developed communication and diplomacy skills are required in order to guide, influence and convince others, in particular colleagues in other areas and occasional external customers. Significant impact on the area through complex deliverables. Provides advice and counsel related to the technology or operations of the business. Work impacts an entire area, which eventually affects the overall performance and effectiveness of the sub-function/job family.

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

------------------------------------------------------

Job Family Group:

------------------------------------------------------

Job Family:

------------------------------------------------------

Time Type:

------------------------------------------------------

Primary Location:

------------------------------------------------------

Primary Location Full Time Salary Range:

In addition to salary, Citi’s offerings may also include, for eligible employees, discretionary and formulaic incentive and retention awards. Citi offers competitive employee benefits, including: medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs. Citi also offers paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays. For additional information regarding Citi employee benefits, please visit citibenefits.com. Available offerings may vary by jurisdiction, job level, and date of hire.

------------------------------------------------------

Anticipated Posting Close Date:

------------------------------------------------------

Citi is an equal opportunity and affirmative action employer.

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.

Citigroup Inc. and its subsidiaries ("Citi”) invite all qualified interested applicants to apply for career opportunities. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi.

View the "EEO is the Law" poster. View the EEO is the Law Supplement.

View the EEO Policy Statement.

View the Pay Transparency Posting