Data Scientist/Application Developer (Secret cleared)

The work:

Key Responsibilities:

• Conduct data discovery and exploratory data analysis across structured and unstructured data
• Perform data cleansing, normalization, aggregation, and modeling
• Design and build analytic applications in Palantir Foundry, including dashboards and interactive workflows
• Apply advanced analytics and statistical methods such as regression, clustering, hypothesis testing, and A/B testing
• Develop and embed AI/ML capabilities (LLMs, NLP, RAG/GraphRAG) into analytic workflows
• Create clear visualizations and metrics to support executive and operational decision‑making
• Collaborate in an Agile/Scrum environment to rapidly iterate on solutions
• Communicate insights effectively to both technical and non‑technical stakeholders

Here is what you need:

• US Citizen (No dual citizenship)
• Active DoD Secret clearance required
• Strong experience in data science and analytics, including EDA, data wrangling, modeling, and statistical analysis
• Proficiency in Python and related analytics/pipeline libraries (pandas, polars, PySpark)
• Experience with AI/ML and statistical modeling tools (scikit-learn, statsmodels, Prophet; NLP tools such as spaCy or NLTK)
• Experience building production-grade analytics solutions (apps, dashboards, notebooks)
• Experience with data visualization using Python libraries or BI tools (matplotlib, seaborn, plotly, PowerBI, Tableau, Qlik)
• Comfort working in a dynamic Agile/Scrum environment with evolving requirements
• Strong communication skills for presenting insights to non‑technical audiences
• Background in statistics, mathematics, operations research, or applied sciences
• Experience with Palantir Foundry, Databricks, or similar data platforms

Preferred experience:

• Hands-on experience with Palantir Foundry (pipelines, transforms, Workshop, Ontologies, AIP)
• Experience building AI-enabled applications using LLMs, NLP, RAG, or GraphRAG
• Experience developing rapid analytic demos with Streamlit
• Familiarity with model deployment and ML/AI serving architectures
• Exposure to TypeScript
• Experience with data platform operations, monitoring, or optimization
• Experience building and maintaining ETL pipelines supporting analytic applications