Risk Data Scientist

Regions Bank

. Research, model, implement, and validate predictive and prescriptive algorithms to analyze diverse data sources .

Posted 9/17/2026full-timeHoover • Alabama • United StatesMid-LevelSenior💰 $101,008 - $145,720 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in predictive and prescriptive modeling, machine learning, and data analytics, with a strong ability to communicate insights and solutions to business leaders. Proficient in managing multiple projects and mentoring junior data scientists while utilizing advanced quantitative techniques to mitigate risks and drive profitable growth.

Highest-signal resume keywords

Predictive ModelingMachine LearningBig Data TechnologiesStatistical AnalysisProject Management

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Predictive ModelingMachine LearningStatistical AnalysisData VisualizationAdvanced SQLData MiningData AnalyticsProgramming (Python, R, SAS)Clustering TechniquesClassification Techniques

Soft Skills

LeadershipCommunicationMentoringProject ManagementBusiness Acumen

Tools & Technologies

HadoopSparkTableauPower BITensorFlowPytorchKerasGoogle AnalyticsAdobe DigitalCI/CD Environments

Industry Keywords

BankingFinancial ServicesQuantitative AnalysisRisk ManagementAgile Software Development

Tech Stack

Tools & technologies

HadoopJavaKafkaKerasPySparkPythonPyTorchRubyScalaSparkSQLTableauTensorflow

About the role

Key responsibilities & impact

Research, model, implement, and validate predictive and prescriptive algorithms to analyze diverse data sources
Mentor and guide junior risk data scientists
Plan and manage multiple concurrent projects
Apply advanced quantitative solutions, models, tools, and analysis to solve complex business problems and manage risks
Work with large, structured, and unstructured datasets
Use quantitative and analytical techniques to support profitable growth and monitor and mitigate risk
Research the ongoing appropriateness of existing or proposed quantitative solutions
Use Big Data tools to build data analytics solutions
Build machine learning and AI models from development through testing and validation
Design rich data visualizations for business leaders and executives
Communicate outcomes and proposed business solutions to senior leaders, external auditors, and prudential regulators
Draw insights from data to support informed decisions
Contribute across all model lifecycle phases, including research, data collection, development, variable selection, implementation, testing, documentation, monitoring, and validation

Requirements

What you’ll need

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, or Ph.D. and four (4) years of related experience
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 tools such as SAS, Python, Ruby, R, Matlab, Scala, or Java
Background in banking and/or other financial services preferred
Experience in Agile Software Development preferred
May require experience in libraries such as TensorFlow, Pytorch, or Keras
Knowledge in Google Analytics and/or Adobe Digital
Advanced Structure Query Language (SQL) skills
Comfortable with 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 ability to communicate with business and 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)

Benefits

Comp & perks

Paid Vacation/Sick Time
401K with Company Match
Medical, Dental and Vision Benefits
Disability Benefits
Health Savings Account
Flexible Spending Account
Life Insurance
Parental Leave
Employee Assistance Program
Associate Volunteer Program