Risk Data Scientist

Thank you for your interest in a career at Regions. At Regions, we believe associates deserve more than just a job. We believe in offering performance-driven individuals a place where they can build a career --- a place to expect more opportunities. If you are focused on results, dedicated to quality, strength and integrity, and possess the drive to succeed, then we are your employer of choice. Regions is dedicated to taking appropriate steps to safeguard and protect private and personally identifiable information you submit. The information that you submit will be collected and reviewed by associates, consultants, and vendors of Regions in order to evaluate your qualifications and experience for job opportunities and will not be used for marketing purposes, sold, or shared outside of Regions unless required by law. Such information will be stored in accordance with regulatory requirements and in conjunction with Regions’ Retention Schedule for a minimum of three years. You may review, modify, or update your information by visiting and logging into the careers section of the system. Job Description: At Regions, the Risk Data Scientist researches, models, implements, and validates algorithms (predictive and prescriptive) to analyze diverse sources of data to achieve targeted outcomes. The position at this level works with multiple teams of data scientists, analysts, and visualization experts and mentors junior risk data scientists as well as independently contributes to solving complex business problems and enabling effective risk management. Additionally, the position at this level requires effective leadership and project management skills as well as in-depth knowledge in quantitative analytical methods, data management, visualization, and programming skills suitable to drive data-driven decisions. Primary Responsibilities • Mentors and guides junior risk data scientists • Plans and manages multiple concurrent projects • Carefully leverages data science, including advanced quantitative solutions, models, tools, and analysis to evaluate and provide solutions to complex business problems and effectively manage a wide spectrum of risks to the company • Works with large, structured, and un-structured datasets • Uses quantitative and analytical techniques to accelerate profitable growth and monitor and mitigate risk- unlocking value across all functional areas of business • Conducts research to evaluate the ongoing appropriateness of existing or proposed quantitative solutions • Uses Big Data tools (e.g. Hadoop, Spark, H2O, CDSW, Domino Labs, etc.) to build data analytics solutions • Builds machine learning and Artificial Intelligence (AI) models from development through testing and validation • Designs rich data visualizations to communicate complex ideas to business leaders and executives • Communicates outcomes and proposed business solutions to senior leaders and other constituencies, including external auditors and prudential regulators • Draws insights from data to make quick, well informed decisions with available information • Demonstrates ability to continuously learn and provide value in a dynamic environment • Works on all phases of model lifecycle, including research, data collection, model development and variable selection, model implementation and testing, model documentation, and ongoing monitoring of model to ensure it is working as intended; shepherds the model through the model validation process This position is exempt from timekeeping requirements under the Fair Labor Standards Act and is not eligible for overtime pay. Requirements • Bachelor's degree and six (6) years of related experience in a quantitative/analytical/STEM field • Or Master's degree and four (4) years of related experience in a quantitative/analytical/STEM field • Or Ph.D. and four (4) years of related experience in a quantitative/analytical/STEM field • Two (2) years of hands-on experience with Big Data technologies such as Hadoop, Hive, Impala, Spark, or Kafka • Three (3) years of working experience with statistical and predictive modeling concepts and approaches such as machine learning, clustering and classification techniques, and artificial intelligence • Three (3) years of working programming experience analyzing large, complex, and multi-dimensional datasets using a variety of tools such as SAS, Python, Ruby, R, Matlab, Scala, or Java Preferences • Background in banking and/or other financial services • Experience in Agile Software Development • May require experience in libraries such as TensorFlow, Pytorch, or Keras • Knowledge in Google Analytics and/or Adobe Digital Skills and Competencies • Advanced Structure Query Language (SQL) skills • Comfortable with both relational databases and Hadoop-based data mining frameworks • Deep understanding of statistical and predictive modeling concepts, machine learning approaches, clustering and classification techniques, and recommendation and optimization algorithms • Expertise in analyzing large, complex, multi-dimensional datasets • Proficient in visualization tools like Power Business Intelligencer (BI) and Tableau • Strong business acumen with the ability to communicate with both business and Information Technology (IT) leaders • Strong leadership and project management skills • Experience with CI/CD environments (Snowflake, Harness, Artifactory, etc.) preferred • Ability to orchestrate large data pipelines efficiently (Spark, Pyspark, Snowpark) Position Type Full time Compensation Details Pay ranges are job specific and are provided as a point-of-market reference for compensation decisions. Other factors which directly impact pay for individual associates include: experience, skills, knowledge, contribution, job location and, most importantly, performance in the job role. As these factors vary by individuals, pay will also vary among individual associates within the same job. The target information listed below is based on the M