We are looking for talented and ambitious individuals to join our large community of quants who are working on a wide range of problems in model development and model risk assessment. Applications areas cover: loss and revenue forecasting, credit decisions, financial crimes, fair lending, operational risks, and stress testing. We use state-of-the-art statistical, mathematical, and machine learning techniques to develop and assess models in these areas. We also use AI techniques (natural language processing, deep learning algorithms, and others) to model information in unstructured data (text, voice and images).
Wells Fargo & Company is a nationwide, diversified, community-based financial services company that is headquartered in San Francisco with major locations around the country. Founded in 1852, Wells Fargo is one of the country’s oldest and most stable companies. We have more than 265,000 team members and serve about one in three households in the United States.
Quantitative Analytics Program (QAP):
This is an early talent program aimed at recruiting new Master’s and PhD graduates and providing them with the opportunity to gain comprehensive professional and industry experience. The Quantitative Analytics Specialist 1 (QAS 1) position is for new Mater’s graduates. As a QAS1, you will work under the supervision of a senior team member to learn how to develop, implement, calibrate, or validate quantitative models covering selected lending products, operational risk processes, or model risk assessment. We provide an exciting and diverse environment where you’ll have the ability to work on interesting and challenging problems. You’ll also have the opportunity to move around the company as you use your problem-solving, organizational and communications skills to build your career.
The program starts in June 2021 with a combination of orientation, classroom training, and professional development activities. Specialists will then be placed in a 12-month rotational program followed by placement within Centers of Excellence involved in Credit or Operational Risks. They will have the opportunity to influence risk management strategies, interact with senior leaders, excel through individual coaching and mentoring, and participate in team building activities. Primary hiring location is Charlotte (NC). Limited hiring opportunities are available in McLean (VA), Minneapolis (MN), Atlanta (GA), and Dallas (TX).
Duties include but are not limited to:
- Performing statistical and mathematical model development and validation (risk assessment) under the direction of experienced team members;
- Using Python, R, SAS, C++, SQL or other programming languages as well as statistical/mathematical packages for model development and validation;
- Producing required documentation to evidence model development or validation;
- Understanding credit and operational risk processes, work flows and issues to sufficiently document and make recommendations for process improvements;
- Understanding business needs and providing possible solutions through clear verbal and written communications to management and fellow team members;
- Participating in model risk projects for varying purposes, methodologies and relevant lines of business;
- Staying current with bank regulatory framework and developments;
- Bringing closure to issues, questions, and requests;
- Collaborating as a member of a team to solve problems that arise; and
- Presenting solutions effectively to a variety of audiences
Wells Fargo will consider only candidates who are presently authorized to work for any employer in the United States and who will not require work visa sponsorship from Wells Fargo now or in the future in order to retain their authorization to work in the United States.
· A Master’s degree in Statistics, Data Science, Economics, Computer Science, Operations Research, Applied or Computational Mathematics, Engineering, or a related quantitative field, with expected graduation date between December 2020 and June 2021;
Other Desired Qualifications:
· Experience and demonstrated first-hand knowledge in a number of these areas: data analysis, statistical modeling, machine learning, data management, and computing;
· Excellent computer programing skills and use of statistical software packages such as Python, R, SAS, C++, and SQL;
· Good verbal and written communication skills as well interpersonal skills;
· Ability to prioritize work, meet deadlines, achieve goals, and work under pressure in a dynamic and complex environment; and
· Ability to develop partnerships and collaborate with other business and functional areas