Principal Full-Stack Data Scientist - Recommendation Algorithms at Jobgether – United States

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Principal Full-Stack Data Scientist - Recommendation Algorithms in the United States.

This role sits at the intersection of advanced machine learning, recommendation systems, and product innovation, shaping how millions of users discover personalized outfits. You will lead the development of next-generation outfit completion models that combine user preferences, stylist expertise, and large-scale behavioral data. The position involves designing and deploying deep learning-driven recommendation systems that optimize relevance, diversity, and contextual awareness across fashion experiences. You will own the full lifecycle of ML systems, from problem framing and experimentation to production deployment and continuous optimization. Working closely with product, engineering, and design teams, you will help define the future of personalized retail experiences. This is a high-impact technical leadership role where your models directly influence user engagement and business outcomes.

• Lead the design and development of outfit completion and recommendation models that power personalized styling experiences.
• Own the end-to-end machine learning lifecycle, including research, model development, deployment, and iteration in production environments.
• Build and optimize deep learning models (e.g., PyTorch-based architectures) for ranking, retrieval, embeddings, and generative recommendation tasks.
• Define experimentation strategies, success metrics, and causal frameworks to evaluate model performance and business impact.
• Leverage large-scale, multi-modal datasets including user behavior, product attributes, and stylist inputs to enhance recommendation quality.
• Collaborate cross-functionally with Product, Engineering, and Design teams to shape roadmap priorities and user-facing features.
• Mentor and guide other data scientists, raising technical standards in modeling, experimentation, and engineering practices.
• Drive innovation in real-time recommendation systems to improve engagement and scalability.

• 5+ years of experience building and deploying machine learning models, including deep learning solutions in production environments.
• Strong expertise in recommendation systems, ranking models, retrieval systems, or related ML domains.
• Hands-on experience with PyTorch or similar deep learning frameworks.
• Proven ability to lead technical initiatives and mentor other data scientists or ML engineers.
• Strong experience in experimentation design, A/B testing, and causal inference methodologies.
• Advanced proficiency in Python and SQL with experience handling large-scale datasets.
• Experience taking ML systems from research through production deployment.
• Strong communication skills with the ability to influence cross-functional stakeholders.
• Ability to operate effectively in ambiguous, high-impact problem spaces.
• Experience with multi-modal data or generative modeling is a plus.

• Competitive salary aligned with senior principal-level data science roles in the US market.
• Annual bonus eligibility and equity-based compensation (including restricted stock units).
• Comprehensive health benefits including medical, dental, and vision coverage.
• Flexible work environment with strong support for work-life balance.
• Opportunity to work on cutting-edge AI-driven recommendation systems at massive scale.
• Strong culture of innovation, ownership, and continuous learning.
• Inclusive, collaborative environment focused on diversity of thought and impact.