Palantir Data Scientist

We are looking for a Data Scientist who can turn business problems into data-driven solutions within Palantir Foundry., * Work with business users to translate needs into measurable data definitions, calculations, models, and outputs.

• Identify when a required business metric is not directly available in source data and create the logic to derive it.

• Develop statistical, analytical, and machine-learning models to support business decisions.

• Create derived datasets, features, scores, aggregations, classifications, or predictions.

• Implement transformations in Palantir Foundry using Python, PySpark, SQL, Code Repositories, Pipeline Builder, or similar tools.

• Understand source-data lineage, relationships, primary keys, and how outputs should connect to the Palantir Ontology and downstream applications.

• Strong practical data-science experience, including statistics, data modeling, feature engineering, and machine learning.

• Experience selecting and applying appropriate methods for real business problems-not only writing code.

• Experience with methods such as random forest, NLP/text analysis (TF-IDF, vectorization, truncated SVD), classification, clustering, forecasting, or similar analytical techniques.

• Strong Python and/or PySpark experience for data transformation and model development.

• Experience creating production-ready datasets and transformations from multiple source systems.

• Ability to explain analytical logic clearly to both technical and business users.

Preferred qualifications:

• Hands-on experience with Palantir Foundry, especially Code Repositories, Pipeline Builder, data lineage, Ontology, and operational applications.

• Experience deploying analytical or ML outputs into business workflows, dashboards, or decision-support tools.

• Experience with unstructured data, document/text analysis, embeddings/vectorization, or computer-vision workflows.

• Automotive, manufacturing, quality, warranty, product-development, or engineering-data experience.

Important distinction: standard data analyst work-mapping fields, identifying keys, connecting datasets, and documenting lineage-is useful but is not sufficient for this role. We need someone who can create the analytical logic and data products that do not already exist in the source systems.

Agent/AIP development is a separate capability and is not required for this position.

This is not a basic data-integration or data-lineage role. The person must be able to understand a business question, identify the required data, develop the mathematical/statistical logic or machine-learning approach, create derived datasets, and implement the solution in Palantir for use in operational applications and reporting.