Risk Data Scientist

Regions Bank•Hoover, AL

1d•$73,528 - $115,260•Onsite

About The Position

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 contributing independently to solve business problems with high complexity and enable effective risk management. Additionally, the position at this level requires in-depth knowledge in quantitative analytical methods, data management, visualization, and programming skills suitable to drive data-driven decisions.

Requirements

Bachelor's degree and four (4) years of related experience Or Master's degree and two (2) years of related experience Or Ph.D. and two (2) years of related experience in a quantitative/analytical/STEM field
One (1) year of hands-on experience with Big Data technologies such as Hadoop, Hive, Impala, Spark, or Kafka
Two (2) years of working experience with statistical and predictive modeling concepts and approaches such as machine learning, clustering and classification techniques, and artificial intelligence
Two (2) 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
Advanced Structured 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 Intelligence (BI) and Tableau
Strong business acumen with the ability to communicate with both business and Information Technology (IT) leaders
Strong communication skills through data visualizations as well as written and oral presentations

Nice To Haves

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

Responsibilities

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
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 Risk Data Scientists
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
Understands all phases of the model lifecycle, ensuring that models and associated documentation comply with model validation expectations