Risk Data Scientist
- 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
- Bachelor's degree and six (6) years of related experience
- Or Master's degree and four (4) 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
- 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
- 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
- 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
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