Tempe, AZ
Lead Quantitative Solutions Engineer Specialist - Credit Risk Data, Reporting & Analytics
At Wells Fargo, we are looking for talented people who will put our customers at the center of everything we do. We are seeking candidates who embrace diversity, equity and inclusion in a workplace where everyone feels valued and inspired. Help us build a better Wells Fargo. It all begins with outstanding talent. It all begins with you.
About this role:
Wells Fargo is seeking a Lead Quantitative Solutions Engineer for the Retail Credit Risk Decisioning Modeling team, a part of Corporate Risk. In this position, you will be a part of the team that is responsible for building, deploying and maintaining the models that are used to manage risk for Wells Fargo's Consumer and Small Business products. Our models cut across the full credit life cycle: from acquisition to account management to collections and recovery, working closely with our partners to make key decisions that affect the bank's bottom line. We use a variety of techniques ranging from traditional regression models to cutting edge machine learning methodologies to develop models that solve today's unique business problems.
In this role, you will:
At Wells Fargo, we believe in diversity, equity and inclusion in the workplace; accordingly, we welcome applications for employment from all qualified candidates, regardless of race, color, gender, national origin, religion, age, sexual orientation, gender identity, gender expression, genetic information, individuals with disabilities, pregnancy, marital status, status as a protected veteran or any other status protected by applicable law.
Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit's risk appetite and all risk and compliance program requirements.
Candidates applying to job openings posted in US: All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process.
About this role:
Wells Fargo is seeking a Lead Quantitative Solutions Engineer for the Retail Credit Risk Decisioning Modeling team, a part of Corporate Risk. In this position, you will be a part of the team that is responsible for building, deploying and maintaining the models that are used to manage risk for Wells Fargo's Consumer and Small Business products. Our models cut across the full credit life cycle: from acquisition to account management to collections and recovery, working closely with our partners to make key decisions that affect the bank's bottom line. We use a variety of techniques ranging from traditional regression models to cutting edge machine learning methodologies to develop models that solve today's unique business problems.
In this role, you will:
- Lead complex activities related to the implementation and ongoing calculation of credit scores from internally built models.
- Effectively execute operational processes, controls, assumptions, metric development, reporting, and growth strategies to successfully drive effectiveness in real time and batch score generation.
- Facilitate the ongoing transformation of our model development and deployment platform and processes using new technology in collaboration with Information Technology partners
- Ensure timely completion, quality, and compliance of projects
- Improve our analytic capabilities by evaluating new tools and techniques and championing their adoption
- Present findings and results verbally and in written form, clearly articulating and defending the rationale behind the recommendations presented
- Collaborate and consult with validators, auditors, and regulators
- Work with compliance and governance to ensure regulatory requirements are met
- Mentor team members on best practices especially with the use of technology
- Be responsible for the implementation, testing, and ongoing maintenance of score generations for credit scoring models
- Deploy predictive models that are created using variety of techniques including logistic regression, gradient boosting, neural networks, etc.
- Work with business partners, model users, and internal teammates to thoroughly understand business problems, develop solutions, and present results.
- Develop complex data preparation programs and investigate and validate data sources.
- Validate the correctness of model input and performance variable generations
- Work with compliance and governance to ensure regulatory requirements are met
- Support other analytic and modeling projects as needed
- 5+ years of Quantitative Solutions Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
- Excellent verbal, written, and interpersonal communication skills
- Experience in working with partners and collaborating with diverse team members representing different functional areas to include Information Technology partners
- Hands-on experience with working on implementation of technical solutions and auditing results using best practices and methodologies in the areas of data processing, sampling, test design/specification, performance assessment, and evaluation testing
- Familiarity with model forms and output particularly with machine learning based models
- Intermediate to advanced coding ability using Python, R, or other open source programming languages as well as data processing using SQL, pandas, PySpark, etc.
- Intermediate to advanced SAS programming skills
- Relevant experience in Retail Business or other risk management modeling area at a major financial institution with a successful track record of accomplishing complex projects is preferred.
- Demonstrated ability to think creatively and work collaboratively
- Strong conceptual and quantitative problem-solving skills
- Ability to effectively work on multiple assignments with challenging timelines
- Experience in tailoring presentations to the intended audience: able to not just present data but tell a story
- Preferred location(s) listed above. Other locations within the Wells Fargo footprint may be considered for current Wells Fargo employees.
At Wells Fargo, we believe in diversity, equity and inclusion in the workplace; accordingly, we welcome applications for employment from all qualified candidates, regardless of race, color, gender, national origin, religion, age, sexual orientation, gender identity, gender expression, genetic information, individuals with disabilities, pregnancy, marital status, status as a protected veteran or any other status protected by applicable law.
Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit's risk appetite and all risk and compliance program requirements.
Candidates applying to job openings posted in US: All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process.
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