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# Principal Full-Stack Data Scientist - Foundational Models

- **Company:** The Ladders
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $200,000.0 - $237,000.0
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Big Data, Python (Programming Language), Machine Learning, Tensorflow, SQL Databases, Pytorch, Large Language Models, Apache Spark, Deep Learning, Model Validation, Machine Learning Operations
- **Published:** October 22, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pthpa3t6x5

## About the Role

* Bachelor's degree in a quantitative field; Master's or PhD preferred
 * 8+ years of experience in machine learning, particularly in personalization
 * Proficiency in Python for production-grade code development
 * Experience with large-scale datasets using SQL and distributed technologies such as Spark
 * Familiarity with deep learning frameworks such as PyTorch or TensorFlow
 * Strong understanding of model evaluation techniques, including A/B testing
 * Excellent communication skills for both technical and non-technical audiences, * Collaborative and innovative work environment
 * Diverse perspectives valued and encouraged
 * Focus on equity and sustainability in all operations
 * Strong team culture with emphasis on relationships and grit
 * Opportunities for professional growth and problem-solving ownership
 * Comprehensive health and wellness benefits

## Description

This role will help shape advanced machine learning capabilities that power personalization and recommendation experiences at scale. You will own work across the full ML lifecycle, from problem framing and experimentation to deployment and monitoring, with a strong focus on foundational modeling approaches. The role also involves partnering closely with cross-functional teams to translate business needs into robust data science solutions that improve model performance and customer outcomes., * Design and productionize machine learning models for personalization and recommendations

 * Advance foundational modeling capabilities such as embeddings and ranking systems
 * Explore and apply advanced ML techniques, including LLMs and generative approaches
 * Manage the full ML lifecycle from problem formulation to deployment and monitoring
 * Conduct rigorous evaluations and experiments to assess model performance
 * Work with large-scale datasets using Python, SQL, and distributed tools
 * Collaborate with cross-functional teams to translate needs into ML capabilities