Job Description:
• Collaborate with data scientists to ensure data is accurately extracted, transformed, and loaded for analysis and decision-making
• Effectively collaborate and partner with various Scores stakeholders to deliver data driven solutions that support strategic Scores initiatives
• Analyze, interpret, and manipulate large data sets to support analytic research and model development efforts
• Deliver high level results supporting business-critical projects within expected timelines
• Use internal technologies in the development, maintenance and improvement of tools and processes to help solve challenging business problems in predictive analytics
• Support the existing code base and the overall analytic SDLC
• Demonstrate self-initiative and innovation by writing new code to continuously evaluate and improve existing code base
• Apply advanced data transformation techniques to optimize the processing of large datasets
• Work closely with the data scientists and other data engineers in constructing the best methodologies in generating new tools, code and datasets based on project requirements
Requirements:
• BS degree in Computer Science, Engineering, Information Technology, Management Information Systems (or equivalent work experience)
• Prior/current experience working with U.S. Credit Bureau data (Preferred)
• Proven programming skills in Python (Highly Preferred), Java/Groovy, Perl and/or Shell scripting
• Demonstrated expertise utilizing Linux (RedHat) and Windows operating systems
• Expertise in AWS services- SageMaker, Jupyter Notebooks, S3, Athena
• Proven expertise analyzing large datasets and applying data-cleaning techniques along with strong data wrangling skills
• Experience working with big data technology (Spark, Hadoop, etc.)
• Familiarity with relational databases (Oracle, mySQL, etc)
• Familiarity with Eclipse IDE
• Familiar with version control tools like GitHub or Bitbucket
Benefits:
• Highly competitive compensation
• Benefits and rewards programs
• Work/life balance
• Employee resource groups
• Social events to promote interaction and camaraderie