Data Scientist (Lending Analytics & Credit Risk)

Navy FederalPensacola, FL
Onsite

About The Position

Navy Federal Credit Union currently does not provide sponsorship for this role. Applicants must be authorized to work in the United States without the need for current or future sponsorship. Provide analytical insights by extracting data through machine learning, programming, data modeling, and advanced mathematics to recognize complex patterns and identify opportunities to drive impact across the organization with a focus on managing credit risk. Developing an understanding of business needs and objectives through the use of basic descriptive, predictive, and prescriptive models. Perform routine assignments with increasing scope and complexity. Work under close supervision with some latitude for problem solving within existing data platforms and tools. Developing professional with basic skill set and proficiency. This position is eligible for the TalentQuest employee referral program. If an employee referred you for this job, please apply using the system-generated link that was sent to you .

Requirements

  • 2-3 years of experience in exploratory data analysis
  • Statistics
  • Programming, data modeling, simulation, and mathematics
  • SQL, R, Python, Hadoop, SAS, SPSS, Scala, AWS
  • Model lifecycle execution
  • Technical writing
  • Data storytelling and technical presentation skills
  • Research Skills
  • Interpersonal Skills
  • Model Development
  • Communication
  • Critical Thinking
  • Collaborate and Build Relationships
  • Initiative with sound judgement
  • Technical (Big Data Analysis, Coding, Project Management, Technical Writing, etc.)
  • Problem Solving (Responds as problems and issues are identified)
  • Bachelor's Degree in Data Science, Statistics, Mathematics, Computers Science, Engineering, or degrees in similar quantitative fields

Nice To Haves

  • Master's Degree in Data Science, Statistics, Mathematics, Computer Science, or Engineering

Responsibilities

  • Design, develop, and evaluate basic/routine predictive models and algorithms with some complexity
  • Analyze and interpret results with some complexity
  • Limited judgment and discretion within defined procedures and practices
  • Develop and code basic software programs, algorithms, and automated processes
  • Use modeling and trend analysis to analyze data
  • Collaborate with team members and participate in team projects and initiatives
  • Utilize effective written and verbal communication to document and present findings
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