1st shift (United States of America) Please review the following job description:
Act as an individual contributor supporting analytics projects and executing against the objectives of assigned business group. Using an interdisciplinary approach of leveraging concepts from business, applied statistics and math, operations research, information technology, process design and behavioral sciences, will work both independently and with internal teammates to produce analytic insights that help the Line of Business (LOB) make informed, data-driven decisions with an objective of driving quantifiable, optimized business results in support of company goals.
Focus on high impact, visible analyses and initiatives across multiple business models, covering banking channels, segments, and products.
Partner on target initiatives as assigned; work independently and with internal teammates to drive decision science projects leveraging quantitative analysis techniques, including machine learning, in pursuit of business optimization and impact.
Pursue business outcomes valued through increased revenue and/or efficiency leveraging data-driven insights powered by analytics in support of enhanced decision-making. Focus on continuous improvement in decision science delivery and outcomes in pursuit of business optimization.
Explore and apply tools to solve business challenges and deliver solutions that are timely, accurate, and repeatable.
Exercise sound judgment, risk management, and foster a client centric culture throughout design, development, and deployment practices.
Foster communication and partnership across multiple levels of the organization including engagement with LOB contributors and junior-level managers.
Requirements
Must have a Bachelor’s degree in Data Science, Analytics, MIS, Computer Science, Statistics or related analytic field.
Must have 4 years of experience in analyst or research positions performing/utilizing the following:
Performing quantitative analysis and data analytics
Statistical methods, including a broad understanding of classical statistics, probability theory, econometrics, time-series, and primary statistical tests
Linear algebra concepts for optimization, complex matrix operations, eigenvalue decompositions, and principal components.
Working knowledge of calculus/differential equations, including use of stochastic processes.
Data cleansing and preparation methodologies, including regex, filtering, indexing, interpolation, and outlier treatment.
Data Analysis techniques, EDA, Data Visualization to effectively communicate to stakeholders, clarify requirements and make effective suggestions.
Data Engineering and ML-Ops to both effectively extract, transform, load the data and for further model deployment, including model maintenance and operation.
Natural Language Processing techniques and other related Deep Learning knowledge.
Utilizing experience with: SQL, SAS, Python, Toad, R, SAS E-Miner, and Tableau.
In the alternative, employer will accept Master’s Degree in in Data Science, Analytics, MIS, Computer Science, Statistics or related analytic field plus 2 years of experience in analyst or research positions performing/utilizing the aforementioned.
Position may be eligible to work hybrid/remotely but is based out of and reports to Truist offices in Atlanta, GA. Must be available to travel to Atlanta, GA regularly for meetings and reviews with manager and project teams within 24-hours’ notice.