SVP, Unsecured Lending Risk Modeling Lead

We, at Citi, believe in the power of Data and the value Data Science can generate for our organization.

Our high-quality financial products and services enable consumers and businesses to prosper and grow in domestic markets, as well as internationally. We put the customers at the center of everything we do and data at the center of how we do it. We continue to combine our scale, digital capabilities, and ecosystem to be where our customers need us to be. Data Science enables us to make our decisions better, faster and our products and services relevant to our customers.
We have made it a priority to foster a culture of inclusion where the best people want to work, where people are promoted on their merits, where we value and demand respect for others, and where opportunities to develop are widely available to all.

Job Description

This position is with Global Consumer Bank (GCB) Risk Modeling Utility. This specific role supports the US Consumer Bank's Lending portfolios, a key growth area for the bank with a focus on digital innovation.

In this role, you will

• Build Machine Learning Models for the Unsecured Lending portfolios and Unsecured Retail Bank products across customer life cycle.
• Partner with a cross-functional team of data scientists, product owners and technology to consult on new capabilities and engage in tool evaluations.
• Leverage a variety of technologies such as SAS, R, Python, H2O, Spark, and more to extract the value out of the data.
• Deliver on all phases of development, from design through training, testing, validation, and implementation
• Practice your presentation and articulation skills to translate the complexity of your work to all types of audience
• Convert a statistical/data science objective function to a clear business goal
• Develop the modeling roadmap for major products and platforms in partnership with product, technology, and design partners
• Be responsible for managing through Internal and External audits
• We will be thrilled to have someone who is
• An experienced Risk Data Scientist -who knows the technicalities and the complexities of the Model Development process and the demands of the Governance and Regulation.
• Creative -who can take a concept and give it shape and structure. Is not afraid to ask questions and loves playing with new ideas.
• Has good Judgment - knows when something does not add up and is not right. Has attention to details and can get into the weeds when needed.
• A Leader - leads by example and is not afraid to challenge status quo. Inspires people with presence. Knows talent when they see it and will do anything to nurture and grow it.

Basic Qualification

• 10 years' experience or less with relevant experience.
• Sound knowledge of statistical modeling concepts and industry best practices; experience with econometric and statistical modeling or application risk scoring.
• Excellent quantitative and analytic skills; ability to derive patterns, trends, and insights, and perform risk/reward trade-off analysis.
• Experience with analytical or data manipulation tools (e.g. SAS, SQL, R, Python, Spark) Proficient with MS Office suite.
• Experience working in Big data environments; Intellectual curiosity to stay abreast of technological advances.
• Ability to deliver compelling presentations and influence executive audiences.
• Excellent communicator: ability to engage and inspire team forward.
• Ability to drive innovation via thought leadership while maintaining end-to-end view.
• Effective cross-functional project, resource, and stakeholder management; effectively engage with internal audit and external regulators

Education:

• Bachelor's/University degree in statistics, mathematics, economics, or equivalent experience. Master's/PhD degree is a plus.

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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.

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