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Data Scientist

Seer
London
2 days ago
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Seer Greater London, England, United Kingdom
This range is provided by Seer. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
We’re looking for a seasoned and inventive Senior Data Scientist to help design and deploy advanced machine learning systems that drive intelligent features in complex real-world domains.
In this role, you’ll lead the development of end-to-end ML pipelines, shape internal modeling strategies, and accelerate the delivery of AI-powered capabilities to production.
You’ll work cross-functionally with product, engineering, and data teams to prototype, evaluate, and implement solutions grounded in rigorous experimentation and practical impact.
Key Responsibilities:
ML & AI Development: Research, build, and deploy machine learning models (including generative AI) focused on structured data, NLP, and time series forecasting.
Model Lifecycle Ownership: Own models from experimentation to deployment, including validation, monitoring, and iteration.
Generative AI & LLMs: Design and evaluate retrieval-augmented generation (RAG) pipelines, embeddings, and fine-tuning strategies using LLMs.
Collaboration & Strategy: Partner closely with product and engineering to translate business problems into data science solutions and deliver impactful features.
Technical Leadership: Contribute to architecture and tooling decisions; mentor junior team members and champion best practices in data science and ML engineering.
Requirements:
ML Expertise: 5+ years of experience in machine learning, data science, or applied AI; strong grasp of supervised/unsupervised learning, deep learning, and probabilistic modeling.
NLP & LLM Skills: Hands-on experience with NLP pipelines, vector stores, transformer models, and generative AI architectures.
Production Experience: Demonstrated success in shipping and maintaining ML models in production, including performance monitoring and optimization.
Strong Programming: Proficiency in Python and ML libraries (e.g., PyTorch, scikit-learn, Hugging Face, etc.); familiarity with MLOps tooling and cloud environments (AWS/GCP/Azure).
Analytical & Communication Skills: Ability to clearly explain complex ideas, trade-offs, and results to diverse audiences.
Nice to Have:
Experience with time series forecasting and modeling irregular structured data.
Background in healthcare, insurance, or other regulated industries.
Familiarity with vector databases, retrieval systems, or multimodal ML architectures.
THIS POSITION DOES NOT SUPPORT RELOCATION OR SPONSORSHIP
Seniority level Seniority level Mid-Senior level
Employment type Employment type Full-time
Job function Job function Information Technology
Industries Technology, Information and Media
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