Creates, validates, tests, documents, implements, and/or oversees usage of complex statistical models. The models may cover a variety of products or services, however, this role's primary purpose is to validate complex statistical models used in the marketing of financial products. Specific results focus on documenting the validation of advanced statistical models and communicating conclusions to stakeholders within the Bank.
This is a highly visible team with an opportunity to make a very meaningful impact on the future direction of the company. Deliverables include the creation of model validation documentation such as: presentations, written reports, model or reporting code documentation, business requirements, monitoring reports and related code, and procedures.
The preferred candidate will have prior model development/validation experience including deployment of machine learning algorithms, proficiency with a range of statistical tools like SAS, R, Python, etc. and sound knowledge of new and emerging analytic tools/technologies (Big data, NLP, artificial intelligence, noSQL databases, deep learning, etc.).
- Bachelor's degree in a quantitative field, and 10 or more years of experience in statistical modeling OR
- Master's or PhD degree in a quantitative field, and six or more years of experience in statistical modeling
? Extensive knowledge of various regression techniques, parametric and non-parametric algorithms, times series techniques, and other statistical models, various model validation tests/methodologies, using SAS, R, Python, etc.
? Advanced data compilation, programming skills and qualitative analysis skills
? Expert in Deep learning architectures e.g. CNN, RNN, LSTM etc.
? Expert in at least one of the following areas: Natural Language Processing, Computer Vision, Speech -Recognition, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis.
? Expertise in one or more major machine learning frameworks: Tensorflow, Caffe/Caffe2, Pytorch, Keras, MXNet, Scikit-Learn.
? Experience in big data technologies: Hadoop, Hive, Spark, Kafka.
? Deep theoretical understanding of Machine Learning
? Thorough knowledge of the quantitative and qualitative risk factors, industry risks, competition risks, and risk management approaches
? Thorough knowledge of applicable regulatory rules, guidance, or supervisory letters
? In depth knowledge of Bank products and services
? Demonstrated independence, teamwork and leadership skills
? Strong analytical, organizational, problem-solving, negotiation, and project management skills
**Primary Location:** Minnesota-MN-Richfield
**Shift:** 1st - Daytime
**Average Hours Per Week:** 40
**Requisition ID:** 190028240
**Other Locations:** United States
U.S. Bank is an Equal Opportunity Employer committed to creating a diverse workforce.
U.S. Bank is an equal opportunity employer committed to creating a diverse workforce. We consider all qualified applicants without regard to race, religion, color, sex, national origin, age, sexual orientation, gender identity, disability or veteran status, among other factors.
* The salary listed in the header is an estimate based on salary data for similar jobs in the same area. Salary or compensation data found in the job description is accurate.