Senior Data Scientist

Full time

Employment Information

Job Description

Provide independent data science, machine learning, and analytical insights using member, financial, and organizational data to support mission critical decision making for the Fraud Analytics team within the Security Department. Understand business needs and identify opportunities for new products, services, and process optimization to meet business objectives through the use of cutting-edge data science, including building machine-learning models to detect fraudulent activity. Create descriptive, predictive, and prescriptive models and insights to drive impact across the organization and enable real-time fraud intelligence decisions. Conduct work assignments of increasing complexity, under moderate supervision with some latitude for independent judgment. Intermediate professional within field; requires moderate skill set and proficiency in discipline.


  • Support the delivery of strategic advanced analytics solutions across the organization with solutions drawing on descriptive, predictive, and prescriptive analytics and modeling
  • Leverage a broad set of modern technologies – including Python, R, Scala, and Spark – to analyze and gain insights within large data sets
  • Manage, architect, and analyze big data in order to build data driven insights and high impact data models
  • Evaluate model design and performance and perform champion/challenger development. Analyze model input data, assumptions, and overall methodology.
  • Using statistical practices, analyze current and historical data to make predictions, identify risks, and opportunities, enabling better decisions on planned/future events
  • Provide analytics insights and solutions to solve complex business problems
  • Apply business knowledge and advanced statistical modeling techniques when building data structures and tools
  • Collaborate with other team members, subject matter experts, pods, and delivery teams to deliver strategic advanced analytic based solutions from design to deployment
  • Examine data from multiple sources and share insights with leadership and stakeholders
  • Transform data presented in models, charts, and tables into a format that is useful to the business and aids in effective decision making
  • Point of contact between the data analyst/data engineer and the project/functional analytics leads
  • Develop and maintain an understanding of relevant industry standards, best practices, business processes and technology used in modeling and within the financial services industry
  • Identify improvements to the way in which analytics service the entire function
  • Recognize potential issues and risks during the analytics project implementation and suggest mitigation strategies
  • Prepare project deliverables that are valued by the business and present them in such a manner that they are easily understood by project stakeholders
  • Perform other duties as assigned


  • Master’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering or another quantitative field, or related field, or the equivalent combination of education, training and experience
  • Ability to understand complex business problems and determine what aspects require optimization and articulate those aspects in a clear and concise manner
  • Advanced skill in communicating actionable insights using data to technical and non-technical audiences
  • Proven experience working in a dynamic, research-oriented groups with several ongoing concurrent projects
  • Demonstrates functional knowledge of data visualization libraries such as matplotlib or ggplot2; knowledge of other visualization tools such as Microsoft Power BI and Tableau
  • Ability to manipulate raw data within visualization tools to create effective dashboards that communicate end-to-end data outcomes visually
  • Proficient in storytelling with data skills
  • Exceptional technical writing skills
  • Advanced skill communicating thoughts, concepts, practices effectively at all levels, adjusting as needed to a target audience
  • Advanced verbal, interpersonal and written communication skills
  • Advanced database, word processing, spreadsheet, and presentation software skills (e.g., Microsoft Access, Excel, PowerPoint, etc.)
  • Moderate skill in descriptive, predictive, and prescriptive analytics and modeling; demonstrated success in building models that are deployed and have made measurable business impact
  • Experience in using two or more of the following modeling types to solve business problems: classification, regression, time series, clustering, text analytics, survival, association, optimization, reinforcement learning
  • Working knowledge of advanced techniques such as: SMOTE, dimension reduction techniques, natural language processing, sentiment analysis, anomaly detection, geospatial analytics, etc.
  • Demonstrates a deep understanding of the modeling lifecycle
  • Moderate skill data mining, data wrangling, and data transformation with both structured and unstructured data; deep understanding of data models
  • Skill interpreting, extrapolating, and interpolating data for statistical research and modeling
  • Advanced skill in Data Interpretation, Qualitative and Quantitative Analysis
  • Advanced skill in Python, R, and/or Scala
  • Moderate skill in SQL and querying (able to pull/transform your own data)
  • Knowledge of cloud computing technologies such as: Apache Spark, Azure Data Factory, Azure DevOps, Azure ML (Machine Learning), Hadoop, Microsoft Azure, Databricks, AWS, Google Cloud
  • Understanding of data models, large datasets, business/technical requirements, BI tools, statistical programming languages and libraries
  • Familiar with Data Engineering concepts
  • Familiar with the use of standard ETL tools and techniques
  • Familiar with the concepts and application of data mapping and building requirements
  • Demonstrates a deep understanding of multiple data related concepts
  • Familiar with Data Integration, Data Governance and Data Warehousing
  • Moderate skill in Data Management, Data Validation & Cleansing and Information Analysis

Desired Qualifications

  • Doctoral degree in Statistics, Mathematics, Computer Science, Engineering or another quantitative field, or related field
  • Working knowledge of Navy Federal Credit Union instructions, standards, and procedures
  • Familiar with project management concepts and frameworks such as Agile Frameworks (SAFE), Communication Strategy and Management, Delivery Excellence and Requirements management

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.

About Us

You have goals, dreams, hobbies, and things you’re passionate about—what’s important to you is important to us. We’re looking for people who not only want to do meaningful, challenging work, keep their skills sharp and move ahead, but who also take time for the things that matter to them—friends, family, and passions. And we’re looking for team members who are passionate about our mission—making a difference in military members' and their families' lives. Together, we can make it happen. Don’t take our word for it:

Disclaimers: Navy Federal reserves the right to fill this role at a higher/lower grade level based on business need. An assessment may be required to compete for this position. Job postings are subject to close early or extend out longer than the anticipated closing date at the hiring team’s discretion based on qualified applicant volume. Navy Federal Credit Union assesses market data to establish salary ranges that enable us to remain competitive. You are paid within the salary range, based on your experience, location and market position.

Bank Secrecy Act: Remains cognizant of and adheres to Navy Federal policies and procedures, and regulations pertaining to the Bank Secrecy Act.


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