Machine Learning Director

US Bank
US Bank

Job Overview

U.S. Bank is looking for a Machine Learning (ML) Director to join the Innovation team, supporting some of the largest initiatives in our company. The ML Director will help design, develop, and bring to production innovative Artificial Intelligence (AI)/ML solutions that will positively impact both our products and our clients. The ML Director is a hands-on role that will be responsible for using the latest in computing and AI/ML technologies to unlock the insights buried within billions of records to transform our customers’ digital experience. The ideal candidate is an experienced technical leader who enjoys optimizing data systems from the ground up, including expanding and optimizing data pipeline architectures and data flows & collections for the AI/ML solutions developed by the Innovation team.This role will work within the fast-paced Innovation team, which strives for excellence in all phases of execution and lifecycle management. The ideal candidate will have the right attitude and an imaginative mind set, is creative, and has extensive experience with AI/ML solution delivery within industry. The individual will be comfortable working in an innovation-focused environment – in particular, evaluating emerging trends and technologies to assess their feasibility and viability and functioning effectively in a fail-fast environment. The position relies on the individual to be a self-starter and a quick learner, to have a futurist mindset, and to be able to innovate and report on tasks and status proactively.Job Responsibilities:* Leads development of ML models to derive insights and make predictions through the entire model lifecycle, from ideation to model deployment and maintenance.* Performs data selection, pre-processing, curation, and extract/transform/load (ETL) of large, complex data sets to support AI/ML solution development.* Creates ML-based tools for analysts/data scientists that convert unstructured to structured data and facilitate data exploration.* Partners with software engineering teams to operationalize ML model outputs within scalable and resilient production systems.* Collaborates with other technical organizations within the company to define optimal data pipelines and identify new growth opportunities using AI/ML technologies.* Encourages new transformative thinking and trail blazing, and facilitates imagination and ideation sessions.* Maintains current knowledge of technology landscape and emerging developments.* Works with various Product and Enterprise teams to optimize customer and user experiences.* Employs practical approach to data access and management and eventual platform integration of AI/ML solutions. Basic Qualifications:* Ph.D. in a STEM field (e.g., Physics, Mathematics, Computer Science, Operations Research, Statistics, or related quantitative/technical fields) and at least 5 years of experience in data engineering, data analytics, and/or data science.* Experience directing the performance of technical experts (e.g. Data Engineers, Data Scientists) in an industry setting (banking/finance industry strongly preferred).* Advanced working knowledge with statistical modeling and data analytics within an industry setting, e.g. Bayesian/Gaussian Distributions, Hidden Markov Models, k-nearest neighbor, etc.* Knowledge of concepts and application of deep learning techniques – e.g CNN’s, RNN’s, LSTM’s and/or RBM’s.* Experience with Python, R, R-Shiny, Tableau, Scala and related open-source technologies such as NumPy, SciPy, Pandas, Scikit-learn, TensorFlow, Keras, Deeplearning4j, etc.* Advanced working knowledge and experience with designing and maintaining both relational and non-relational databases and data access methods, e.g. Postgres, MongoDB, SQL, NoSQL, RESTful API’s, GraphQL, etc.* A successful history of manipulating, processing, and extracting value from large distributed and unstructured datasets.* Experience with API’s or software packages for computer vision and/or NLP, e.g. OpenCV, Gensim, BERT, SpaCy, NLTK.* Knowledge of programming and software design fundamentals, e.g. object oriented and functional design principles, best practices, etc.* Experience in developing within cloud-based environments (e.g. Google Cloud, Amazon Web Services, Microsoft Azure), with emphasis on GPU-enabled computing.* Experience delivering and maintaining AI/ML solutions in production using Continuous Integration/Continuous Delivery (CI/CD) tools (e.g. Jenkins, Kubernetes, GitHub, JIRA/Bitbucket/Bamboo, Artifactory, DataDog) and best practices.* Experience delivering communications in a clear, concise, and compelling manner.* Willing to travel up to 25% of the time for business purposes.

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