Data Scientist

Analytics And Data Science Professional You will be joining a team of analytics and data science professionals within the Enterprise Data & Analytics organization. Team members are highly skilled in a mixture of R, Python, SAS, SQL, Tableau, and Adobe Analytics/Target to perform modeling, visualization, and advanced analytics. Members of the team primarily support the Digital and Omnichannel organizations but are strategically positioned to partner with and support nearly every part of the company including Product, Marketing, Consumer Sales and Operations, Business and Commercial Banks, Private Client Group, Enterprise Payments, and IT. We align with our partners within the Agile development framework and support projects throughout their entire lifecycle from ideation through delivery on the largest and most visible projects undertaken at the company. This highly visible and critical role will be set in a fast-paced environment with the ability to influence not just any single project but the overall direction of the organization. Duties And Responsibilities Ability to use advanced analytics methods to extract value from business data. Ability to perform large-scale experimentation and build data-driven models to answer business questions. Conducts research on cutting-edge techniques and tools in machine learning/deep learning/artificial intelligence. Determines requirements that will be used to train and evolve deep learning models and algorithms. Influences product teams through presentation of data-based recommendations. Performs other duties as assigned. Basic Qualifications Master's degree completed by Spring 2025 in Computer Science or Information Systems, Decision Sciences, Statistics, Operations Research, Applied Mathematics, Engineering, or a STEM degree or in lieu of a Master's degree, Bachelor's degree with a minimum of 3 years work experience in analytics or data science Experience with R, RStudio, Python, SAS, SQL, NoSQL Preferred Qualifications Up-to-date knowledge of machine learning and data analytics tools and techniques Knowledge in predictive modeling methodology Experienced at leveraging both structured and unstructured data sources Willingness and ability to learn new technologies on the job Work and/or educational experience conducting statistical analysis with advanced statistical software, scripting languages, and packages Work and/or educational experience with big data analysis tools and techniques Foundational knowledge of building and deploying predictive models, web scraping, and scalable data pipelines Understanding of statistical methods and skills such as Bayesian Networks Inference, linear and non-linear regression, hierarchical, mixed models/multi-level modeling Experience with Cloud Machine Learning technologies (e.g., AWS Sagemaker) Experience with machine learning environments (e.g., TensorFlow, scikit-learn, caret) Financial Services background About Candidate A curious mind with a thirst for discovery, answers, optimization, and continuous improvement Excellent written and verbal communication skills with a proven ability to interact effectively across all organizational levels Creative thinker and problem solver, with a strong ability to manage ambiguity/complexity Work effectively in teams as well as independently across multiple tasks while meeting aggressive timelines Experience working in a consumer-centric company and with teams of technical professionals in a cross-functional environment