Lead Quantitative Analytics Specialist

About this role:

Wells Fargo is seeking a Lead Quantitative Analytics Specialist.

MRM operates in a fast-paced work environment with continuously changing policies and technologies. The successful candidate is expected to be self- motivated, require minimal supervision, and produce work that is consistent with MRM's recognized high standards. Effective work will involve familiarity with source systems of record, analytical data and sampling plans, model replications, model performance assessments, and test model development as effective challenges to lines of business. It further requires strength in writing detailed standard analytical reports to ensure Wells Fargo's compliance with governance policies and regulations. Each validation report will include assessments of the specific business, model purpose and history, the model methodology, data integrity, model development, performance, implementation, and monitoring. These documents are read by a broad audience, including auditors and regulators.

In this role, you will:

• Lead complex initiatives including creation, implementation, documentation, validation, articulation, and defense of highly statistical theory

• Qualify monitor markets and forecast credit and operational risks

• Strategize short and long-term objectives, and provide analytical support for a wide array of business initiatives

• Utilize stochastic, structured securities, spread analysis, with the expertise in the theory and mathematics behind the analysis

• Review and assess models inclusive of technical, audit, and market perspectives

• Identify structure and scope of review

• Enable decision making for product and marketing with broad impact and act as key participant to develop and document analytical models

• Collaborate and consult with regulators and auditors

• Present results of analysis and strategies

Required Qualifications:

• 5+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

• Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science

Desired Qualifications:

• 5+ years of experience with minimum Masters/Phd in a quantitative field such as applied math, statistics, engineering, physics, or mathematical finance.

• Performing mathematical model validation using Python, C++, R, and SQL or other programming languages and mathematical/statistical packages

• Producing required documentation to substantiate model validation

• Analyzing processes and work flows to make recommendations for process improvement in various risk management and/or business areas as well as participating in and leading model risk projects

Job Expectations:

• Understanding of the larger counterparty credit risk models, business context, and an ability to translate business context into modelling requirements.

• Strong mathematical, statistical, analytical and computational skills

• Strong communication skills for a variety of audiences (other technical staff, senior management and regulators) both verbally and in writing

• Capability to multi-task and finish work within strict timelines and provide timely requests for information and follow-up questions

• Ability to work independently on complex model validations from start to finish

• Able to demonstrate first-hand knowledge of advanced topics in various mathematical and numerical methods such as Monte Carlo, stochastic calculus, differential equations, linear algebra, applied probability, and statistics

• Skill in managing relationships with key model stakeholders

• Eagerness to contribute collaboratively on projects and discussions

• Perpetual interest in learning something new, but being comfortable with not knowing the all the answers

• Attention to detail in both analytics and documentation

• Aptitude for synthesizing data to form a story and align information to contrast/compare to industry perspective

• Intellectually curious, who enjoy solving problems

• Excellent programing skills and use of software packages such as C++, Python, R, SAS and SQL

• Ability to prioritize work, meet deadlines, achieve goals, and work under pressure in a dynamic and complex environment

• Good interpersonal skills and ability to develop partnerships and collaborate with other business and functional areas

Posting End Date:

We Value Equal Opportunity

Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.

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 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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b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.