At Regions, the Risk Data Scientist researches, models, implements, and validates algorithms to analyze diverse sources of data to achieve targeted outcomes and enable effective risk management.
Requirements
- One year of hands-on experience with Big Data technologies such as Hadoop, Hive, Impala, Spark, or Kafka
- Two years of working experience with statistical and predictive modeling concepts and approaches such as machine learning, clustering and classification techniques, and artificial intelligence
- Two 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
- Proficient in visualization tools like Power Business Intelligence (BI) and Tableau
Responsibilities
- Works with large, structured, and un-structured datasets
- Uses quantitative and analytical techniques to accelerate profitable growth and monitor and mitigate risk
- Uses Big Data tools 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
Other
- Bachelor's degree and four years of related experience, or Master's degree and two years of related experience, or Ph.D. and two years of related experience in a quantitative/analytical/STEM field
- 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
- Ability to continuously learn and provide value in a dynamic environment
- Background in banking and/or other financial services (preferred)
