Overview
Team Overview: The Data Science Management (DSM) team within the Collections department works under Workforce Strategy as a part of the larger Collections Strategy Management department. Our team applies advanced statistics and analytics to predict several different key metrics across the Collections organization. As a part of the Workforce Strategy department, many of our projects are focused on the staff and workload of delinquent accounts.
Work on the team includes:
• Exploring and validating data sources across multiple platforms
• Preparing model ready datasets through various ETL processes
• Developing advanced statistical models of key metrics, producing usable forecasts
• Document and communicate models effectively to technical and non-technical business users.
• Monitor and maintain models, evaluate performance and error.
• Understand business practices and trends, and their impact to existing and future models.
• Provide quantitative and qualitative analysis to the business.
Potential Project:
This role will be a member of the Data Science Management team within Collections Workforce Strategy. The team primarily focuses on modeling and forecasting key metrics surrounding delinquency and our collections strategy. This role will have direct impact in building a business ready model and forecast and will require collaboration with senior Data Scientists on the team.
The Summer Associate would be responsible for learning the business and data landscape for the specific delinquency metric they will be modeling. This requires building the model ready dataset, analyzing the data for accuracy and trends. Once the model ready dataset has been produced, a model will be developed and forecast created.
The Summer Associate Program is a 12-week internship program beginning in May 2025 and ending in August 2025. Students will work on impactful projects and meaningful work during their internship. To qualify for this position, applicants must be currently pursuing a degree from an accredited college or university and have an anticipated graduation date of December 2025 or later.
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.
Qualifications
Business Skills:
• Excellent communication skills
• Self-starter with significant experience in managing multiple priorities independently.
• Significant experience in problem resolution including determining root cause, scope, and scale of issues.
• Experience that demonstrates the ability to research, compile, and document data, business processes, and workflows.
• Advanced skill in maintaining accuracy with high attention to detail.
• Advanced research, analytical, and problem-solving skills
• Advanced presentation, verbal, and written communication skills advanced skill in identifying and analyzing business requirements and recommending solutions.
• Significant experience in managing cross-functional, multi-dimensional teams and projects of the highest complexity with high business risk and impact.
• Advanced skill in analyzing statistics and reports to determine business performance, trends, and reporting.
• Advanced skill in data mapping and building requirements.
Technical skills:
• Currently pursuing a graduate degree in Statistics, Mathematics, Economics, Data Science, Data & Analytics, Computer Science, or other STEM related degree
• Advanced skill in interpreting, extrapolating, and interpolating data for statistical research and modeling
• Advanced knowledge and experience with time series modeling (ex. ARIMA, Linear Regression, OLS, Holt-Winters, TBATS)
• Advanced skill in Data Interpretation, Qualitative and Quantitative Analysis
• Advanced skill in Python, SQL, and Data Querying (able to pull/transform data)
• Advanced knowledge of cloud computing technologies such as: Apache Spark, Azure Data Factory, Azure DevOps, Azure ML (Machine Learning), Microsoft Azure, Databricks
• Advanced skill in data mining, data wrangling, and data transformation with both structured and unstructured data; deep understanding of data models
• Advanced skill in programming languages and databases
• Familiarity with Data Engineering concepts (ex: ETL tools and techniques)
• Advanced skill in Data Management, Data Validation/Cleansing, and Information Analysis
About Us
Navy Federal provides much more than a job. We provide a meaningful career experience, including a culture that is energized, engaged and committed; and fierce appreciation for our teams, who are rewarded with
Location: Pensacola, FL
Posted: Sept. 23, 2024, 8:29 p.m.
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