Principal Data Scientist (PySpark & Palantir Foundry) (Oakland)

Principal Data Scientist (PySpark & Palantir Foundry) – Oakland, CA, USA

Required Education

• Master's Degree in Data Science, Machine Learning, Computer Science, Statistics, Electrical Engineering, Mechanical Engineering, Civil Engineering, or a related quantitative field.

Preferred Education

• Doctoral (Ph.D.) degree in Data Science, Machine Learning, Computer Science, Statistics, Electrical Engineering, Mechanical Engineering, Civil Engineering, or a related field.

Required Experience

• 8+ years of professional experience developing and deploying machine learning and advanced analytics solutions (or 2+ years with a Ph.D.).
• Experience designing, building, and maintaining scalable predictive models using Python or PySpark.
• Experience extracting, transforming, and integrating large structured and unstructured datasets from multiple enterprise data sources.
• Experience developing reusable, production‑quality code and documenting data science solutions for enterprise use.
• Experience collaborating with cross‑functional business and technical teams to deliver analytics‑driven solutions.

Preferred Experience

• Experience designing and managing complex data pipelines using Palantir Foundry.
• Experience developing user‑facing applications or dashboards that enable business users to interact with advanced analytics.
• Experience within the electric utility, gas utility, energy, infrastructure, or data science consulting industries.
• Experience applying time‑series analysis, causal inference, probabilistic risk assessment, or experimental design techniques to real‑world business problems.
• Experience mentoring technical teams, conducting model reviews, and supporting Agile product development practices.

Required Skills

• Advanced proficiency in PySpark and Python.
• Strong knowledge of machine learning, feature engineering, statistical modeling, and data preparation techniques.
• Ability to develop scalable, modular, and maintainable code following software engineering best practices.
• Strong analytical and problem‑solving skills with the ability to translate business requirements into technical solutions.
• Excellent communication and cross‑functional collaboration skills with both technical and non‑technical stakeholders.

Preferred Skills

• Expertise with Palantir Foundry platform.
• Full‑stack development skills for building intuitive user interfaces and analytics applications.
• Knowledge of supervised, unsupervised, deep learning, and physics‑based modeling techniques.
• Experience with model evaluation, optimization, deployment pipelines, and MLOps best practices.
• Familiarity with AWS, code reviews, open‑source development, and industry data science standards.
• Strong leadership, mentoring, and technical coaching abilities.

Key Responsibilities

• Design, develop, and deploy scalable machine learning and predictive analytics solutions for enterprise risk management.
• Build and optimize data pipelines to prepare, transform, and integrate data from multiple enterprise systems.
• Develop reusable algorithms, models, and software components that support business decision‑making.
• Design statistical methodologies and evaluate model performance to ensure accuracy, scalability, and reproducibility.
• Partner with business stakeholders to identify opportunities and translate complex business problems into data‑driven solutions.
• Present analytical findings and technical recommendations to leadership and cross‑functional teams.
• Review complex models, promote engineering best practices, and contribute to continuous improvement of data science capabilities.
• Only those lawfully authorized to work in the designated country associated with the position will be considered.
• Please note that all Position start dates and duration are estimates and may be reduced or lengthened based upon a client’s business needs and requirements.

Equal Opportunity Employer

Rose International is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, sexual orientation, gender (expression or identity), national origin, arrest and conviction records, disability, veteran status or any other characteristic protected by law. Positions located in San Francisco and Los Angeles, California will be administered in accordance with their respective Fair Chance Ordinances.