Remote Principal Full-Stack Data Scientist – Personalization

Ladders; États-Unis; À distance; USD 200 000 - 237 000; Plein temps

Avantages offerts par ce poste

Health benefits

Inclusive culture

Growth opportunities

Flexible work environment

Impact in retail tech

Résumé du poste

Ladders is seeking a Principal Full-Stack Data Scientist focused on Foundational Models to advance personalization and recommendations at scale. You will own end-to-end ML work from problem framing to deployment, partnering with cross-functional teams to translate behavioral data into scalable, high-impact solutions.

This role is remote for US-based candidates only, with a compensation range of $200,000 to $237,000 annually.

Qualifications

• Bachelor's degree in a quantitative field; Master's or PhD preferred.
• 8+ years of experience in machine learning solutions, particularly in personalization.
• Experience with large-scale datasets using SQL and distributed technologies like Spark.

Responsabilités

• Design and develop machine learning models to enhance personalization and recommendations.
• Advance foundational modeling capabilities such as client representations and recommendation models.
• Explore and implement advanced ML techniques, including deep learning and generative approaches.
• Manage the full ML lifecycle from problem formulation to deployment and monitoring.
• Conduct rigorous evaluations and experiments to assess model performance and impact.
• Utilize large-scale behavioral datasets with Python, SQL, and distributed tools.
• Collaborate with cross-functional teams to translate needs into foundational ML capabilities.

Connaissances

Python

SQL

Distributed computing

Deep learning

A/B testing

Communication

Formation

Bachelor's degree in a quantitative field

Master's or PhD preferred

Outils

PyTorch

TensorFlow

Apache Spark

Description du poste

Ladders is seeking a Principal Full-Stack Data Scientist focused on Foundational Models to advance personalization and recommendations at scale. You will own end-to-end ML work from problem framing to deployment, partnering with cross-functional teams to translate behavioral data into scalable, high-impact solutions.

This role is remote for US-based candidates only, with a compensation range of $200,000 to $237,000 annually.