Job Details

Overview

Data Scientist-16094 – Hybrid

The requisition is open to all campus locations - HQ (Vienna, VA), WOC (Winchester, VA), GPO (Pensacola, FL), SDO (San Diego, CA) for a Hybrid role only - no remote work or Microsites.

Our Digital data science department is dedicated to building predictive solutions for our mobile applications and online business operations. We develop predictive tools to assist business and app developers in enhancing user experience and optimizing operational performance.

We are seeking a motivated and talented mid-level experienced (3-7 yr) data scientist to join our growing department. This role involves collaborating with senior team members, leaders, and business units to create custom solutions and data science models that provide insights into customer digital behavior, forecast mobile app and website usage trends, assess customer app store sentiment, and analyze data for actionable insights. Knowledge or insights into financial services and banking products will also be helpful in designing solutions and predictive tools to help customers improve financial management and financial health/well-being.

Responsibilities

• Collaborate with senior data scientists and leaders to design and implement predictive models and custom solutions that enhance our digital offerings.
• Partner with business units to gather requirements, understand customer needs, and develop data science solutions that address specific business challenges.
• Write efficient code in Python and SQL to manipulate and analyze data.
• Design, develop, and evaluate predictive models and algorithms with moderate to high complexity.
• Utilize traditional and machine learning techniques and tools to build a variety of models, including but not limited to logistic regression, random forest, XGBoost, neural networks, NLP, k-means clustering, ARIMA, and prophet forecasting.
• Analyze and interpret results with some complexity.
• Exercise limited judgment and discretion within defined procedures and practices.
• Develop and code modeling 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

• 3-7 years of experience (mid-level) in data science, statistics, and data analytics.
• Ability to work with moderate to minimal supervision.
• Strong programming abilities in SQL, Python, PySpark, R, or similar languages in data exploration, data preparation, modeling, prediction, simulation, and statistical analysis.
• Experience with machine learning techniques and tools to build a variety of models, including logistic regression, XGBoost, neural networks, NLP, and clustering.
• Ability to use data and cloud environments such as Azure, Databricks, AWS, or Hadoop.
• Familiarity with project management tools such as Azure Dev Ops (ADO), or JIRA is a plus.
• Technical writing skills.
• Strong communication and data storytelling presentation skills of technical material.
• Ability to collaborate and build relationships.
• Required: Bachelor's degree in data science, statistics, economics, mathematics, computer science, engineering, or degrees in similar quantitative fields.
• Desired: Master's degree in data science, statistics, mathematics, or degrees in similar quantitative fields.