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# Senior Data Scientist

- **Company:** Mark Spencer
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Big Data, Customer Data Management, Distributed Computing Environment, Machine Learning, Recommender Systems, Software Engineering, Large Language Models, Apache Spark, Machine Learning Operations
- **Published:** August 26, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pfdymgnu3m

## About the Role

We are seeking a highly skilled and innovative Senior Data Scientist to join our Recommendations team within Customer Data Science, building the next generation of personalised product recommendations, outfit suggestions, and our AI Stylist conversational experiences, to help millions of users find products that they will love. Your work will directly drive higher customer satisfaction, conversion rates, and commercial impact as part of M&S's digital transformation., * Proven track record of owning ML/AI problems end-to-end - from framing and modelling through to production deployment, monitoring, and continuous improvement - delivering measurable business impact.

 * Applies strong software engineering principles to build robust, scalable ML systems, taking responsibility for performance and reliability in production rather than handing off.
 * Experience working with large-scale datasets and distributed data processing (e.g. Spark), and with modern recommendation or personalisation systems (e.g. large-scale retrieval and ranking architectures, real-time inference, vector representations, approximate nearest-neighbour search) at scale.
 * Strong collaborator and communicator, comfortable working across Product, Engineering, and business teams.

## Description

* Use machine learning, recommender systems, and LLM-powered conversational AI to deliver deeply personalised product and outfit recommendations.
 * Design, develop, and productionise end-to-end ML and GenAI systems, including retrieval, ranking, and LLM-based components powering conversational experiences
 * Design and develop frameworks for evaluating LLM outputs (e.g. relevance, grounding, safety, and user satisfaction) and integrate them into continuous experimentation pipelines.
 * Partner cross-functionally to deliver production-ready solutions aligned to product and commercial goals.
 * Contribute to best practices in model development, deployment, and monitoring across the team.


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