Data Scientist II (Model Validation, Remote)
YOUR LIFE'S MISSION: POSSIBLE
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.
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Provide independent data science, machine learning, and analytical insights using member, financial, and organizational data to support mission critical decision making for various areas of the organization. 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. Create descriptive, predictive, and prescriptive models and insights to drive impact across the organization. Regarded as an advanced professional in the data science field. Conduct complex work under minimal supervision and with wide latitude for independent judgment. Individual contributor and mentor to junior staff.
Model Risk Management
Provide independent effective challenge to the models developed by the organization’s business units. This includes conducting model validation, statistical analyses, building benchmark/challenger models, assessing model risk, assessing model performance, ensuring documentation completeness, and identifying and presenting findings to various stakeholders within the business units. Regarded as an advanced professional in the data science field. Conduct complex work under minimal supervision and with wide latitude for independent judgment. Individual contributor and mentor to junior staff.
Advanced Analytics Focused
- 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
Model Risk Management
- Conduct model validations, assess model performance, and evaluate model conceptual soundness, including input data, assumptions, statistical and analytical testing, and general development methodology
- Conduct model outcomes analysis, including backtesting
- Assess new and existing model’s overall fit/suitability with its intended use and purpose
- Provide subject matter expertise to identify models’ key assumptions, limitations and weaknesses, and recommend practical solutions to mitigate model risk
- Develop benchmark/challenger models to assess strength of model under review
- Prepare and present clear, thorough reports to model developers and model owners explaining the analysis performed, results of the analysis and recommendations for improvement
Qualifications and Education Requirements:
All Data Scientist Roles
- 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
- Significant experience working in a dynamic, research-oriented groups with several ongoing concurrent projects
- Demonstrates advanced 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
- Advanced storytelling with data skills
- Exceptional technical writing skills
Advanced Analytics Focused
- Advanced skill in descriptive, predictive, and prescriptive analytics and modeling; demonstrated success in building models that are deployed and have made measurable business impact
- Significant 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
- Advanced 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
- Advanced skill data mining, data wrangling, and data transformation with both structured and unstructured data; deep understanding of data models
- Advanced 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
- Advanced skill in SQL and querying (able to pull/transform your own data)
- Advanced 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
- Advanced skill in Data Management, Data Validation & Cleansing and Information Analysis
Model Risk Validation
- Significant experience R or Python or Spark to analyze large data sets and develop predictive models
Desired Qualifications and Education Requirements:
All Data Scientist Roles
- Doctoral degree in Statistics, Mathematics, Computer Science, Engineering or another quantitative field, or related field, or the equivalent combination of education, training and experience
- Experience with CECL, CCAR, PPNR, ALLL, and/or Scorecard
- 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
Hours: Monday - Friday, 8:00 am - 4:30 pm
Location: 820 Follin Lane, Vienna, VA 22180 | 5550 Heritage Oaks Dr Pensacola, FL 32526 | 141 Security Dr. Winchester, VA 22602 | Remote
Navy Federal is now hybrid! Our standard enterprise requirement for a hybrid schedule is to report onsite 4-16 days each month. The number of days reporting onsite will ultimately be determined by the employee's leadership and business unit needs. You will learn more throughout the hiring and onboarding process.
Salary: 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.
The salary range for this position is: $95,600 to $179,700 Annual Salary #LI-Remote
Equal Employment Opportunity
Navy Federal values, celebrates, and enacts diversity in the workplace. Navy Federal takes affirmative action to employ and advance in employment qualified individuals with disabilities, disabled veterans, Armed Forces service medal veterans, recently separated veterans, and other protected veterans. EOE/AA/M/F/Veteran/Disability
COVID-19 Vaccine Information
As a COVID-19 safety measure, our employees must either provide proof of COVID-19 vaccination or follow additional safety protocols, including testing.
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.
Bank Secrecy Act
Remains cognizant of and adheres to Navy Federal policies and procedures, and regulations pertaining to the Bank Secrecy Act.
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.