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# Associate Data Scientist/ Data Scientist

- **Company:** U.S. Navy
- **Location:** Vienna, VA, United States
- **Experience:** Experienced
- **Salary:** $70,000.0 - $118,050.0
- **Contract:** Internship / Graduate position
- **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Microsoft Azure, Computer Programming, Data Presentation, Database Queries, R (Programming Language), Python (Programming Language), Logistic Regression, Machine Learning, Natural Language Processing, Productivity Software, Recommender Systems, Software Tools, Standard Sql, Azure Machine Learning, Sentiment Analysis, SQL Databases, Google Cloud, Prophet, Large Language Models, Random Forest, Build Management, Information Technology, Xgboost, GPT, K Means, Databricks
- **Published:** September 1, 2026
- **Apply:** https://www.dice.com/job-detail/f1463f4b-17f4-4381-bfee-9205ff936ff3

## About the Role

We are seeking a motivated early- to mid-career Data Scientist who is passionate about solving real-world business problems through data. This role is ideal for someone who enjoys combining statistical analysis, machine learning, experimentation, behavioral analytics, and emerging AI capabilities to uncover insights and drive measurable impact., * Bachelor's Degree in Data Science, Statistics, Applied Mathematics, Computer Science, Engineering, or degrees in similar quantitative fields

 * 1-4 years' experience conducting data science, business intelligence, analytics, or statistical analysis related project work
 * Basic programming experience in data modeling and database management
 * SQL, Python, R
 * Experience using AI tools such as Copilot, Claude, ChatGPT, Azure AI Foundry, LangChain, Semantic Kernel, Azure AI Services, or similar frameworks
 * Familiarity with machine learning concepts including classification, logistic regression, clustering models like k-means, tree-based models like random forest or XGBoost, recommendation systems, NLP, and sentiment modeling
 * Familiarity with traditional modeling techniques such as regression, logistic models, or time series models such as ARIMA or Prophet
 * Experience using cloud analytical environments such as Azure, Databricks, AWS, or Google Cloud Platform
 * Strong curiosity and ability to learn new technologies quickly
 * Excellent communication and storytelling skills, * Master's Degree in Data Science, Statistics, Applied Mathematics, Computer Science, Engineering, or degrees in similar quantitative fields
 * Strong Python skills
 * Strong SQL skills
 * Data storytelling and technical presentation skills

## Description

As a member of our team, you will collaborate with cross-functional partners across product, technology, and business teams to transform complex questions into actionable insights. Our team draws from a broad range of analytical, machine learning, and AI techniques to deepen understanding of member behavior and digital experiences. This work spans areas such as digital experience analytics, customer feedback and sentiment analysis, digital usage forecasting, member behavior modeling, feature adoption measurement, and operational optimization, helping drive better decisions, improve member outcomes, and enhance the digital experience for millions of members., * Analyze member digital behavior using Python and SQL

 * Conduct exploratory data analysis to identify patterns in product adoption, engagement, and customer experience
 * Partner with business stakeholders and product teams to solve digital experience challenges
 * Build and deploy analytical solutions that provide actionable business insights
 * Assist in development of predictive and machine learning models
 * Support AI-powered summarization and classification workflows using large language models
 * Support agent-building solutions for workflow automation and productivity tools
 * Develop NLP and sentiment analysis solutions using customer feedback data
 * Analyze app reviews, surveys, contact center data, social media, and digital feedback sources
 * Communicate findings through reports, presentations, dashboards, and storytelling
 * Collaborate with senior data scientists to design and evaluate advanced analytical solutions
 * Knowledge of financial services, digital products, or customer experience analytics is beneficial but not required


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