Data Scientist

About Chattermill: Chattermill is a premier, internationally recognized customer experience (CX) intelligence platform pioneer, deep learning innovator, and enterprise text analytics leader on an absolute mission to help large, successful global brands like Uber, Amazon, Wise, and HelloFresh put their consumers at the absolute center of everything they do. By leveraging best-in-class neural architectures in a fast-developing AI space, Chattermill’s cloud platform continuously processes and analyzes massive volumes of explicit and implicit user feedback strings. Operating under an ownership-driven culture, Chattermill unifies advanced machine learning algorithms with frictionless engineering pipelines, transforming unstructured text anomalies into clear, data-driven actionable strategies that maximize retention, protect client interests, and eliminate poor user experiences globally.

Position Overview

We are seeking a highly sophisticated, mathematically minded Data Scientist to join our core global Data Science division in a full-time remote or hybrid capacity within the United Kingdom. In this high-agency engineering seat, you will report to our Chief Scientist, Aji, claiming absolute individual accountability for building, training, and shipping the next generation of our proprietary AI intelligence stack. Shifting entirely away from basic third-party API dependencies, Chattermill develops custom fine-tuning pipelines and bespoke models specialized across various extraction, retrieval, reranking, summarization, and sentiment analysis workflows. This role demands a rising machine learning specialist who writes clean, well-tested code, demonstrates full-stack technical curiosity, and balances off-the-shelf Large Language Models (LLMs) with classical statistical principles to deliver high-fidelity system-level results.

Key Responsibilities

• Bespoke Model Fine-Tuning: Train, evaluate, and iterate on custom machine learning models explicitly specialized for consumer text classification, semantic retrieval, and multi-lingual sentiment analysis tasks.
• LLM Feature Architecture: Design and maintain LLM-powered features, building out state-of-the-art embedding pipelines, reranking systems, and automated insight generation modules alongside senior team members.
• PyTorch Execution and Experiments: Write, test, and optimize advanced model training loops and fine-tuning pipelines natively using the PyTorch language framework.
• Semantic Search Curation: Construct scalable semantic search layers, developing a strong working command of embedding-based tokenizers and generative retrieval approaches that go beyond typical keyword lookups.
• Rigorous Evaluation Frameworks: Build out comprehensive test gold-standards, define algorithmic performance metrics, and audit model quality across text classification, data extraction, and generative language tasks.
• Engineering Stack Integration: Collaborate directly with internal Software Engineering squads on production model integration steps, real-time data pipelines orchestration, and ongoing cloud model monitoring layers.
• Research Literature Synthesis: Stay close to relevant academic AI research, tracking advancements in deep learning literature and proactively presenting useful methods during team experiment discussions.
• Agile Backlog Alignment: Partner across cross-functional Data Science, Engineering, and Product teams to translate complex business requirements into structured, actionable machine learning hypotheses.

Required Skills & Qualifications

• Proven professional history running applied Data Science, machine learning engineering, natural language processing (NLP) application architecture, or quantitative algorithm modeling.
• Deep, authoritative technical command of modern **transformer architectures** and how neural attention mechanisms are applied in text extraction and processing fields.
• Hands-on production proficiency engineering model training workflows and setting up specialized code blocks natively inside PyTorch.
• Demonstrated experience working with real-world text datasets across tasks like classification, text extraction, semantic embeddings, or search at a meaningful scale.
• Familiarity with generative AI patterns, prompt engineering frameworks, and basic instruction fine-tuning or agentic software architectures.
• Outstanding verbal and written communication mechanics, with a clear capability to interpret complex mathematical work and explain technical abstractions to non-technical business colleagues.
• Location Context: Full-time parameters open exclusively to qualified machine learning professionals based permanently within the United Kingdom to execute from home or via our London office under a choice-first model.

Preferred Strategic Indicators (Nice to Have)

• An MSc or higher technical degree focused natively on Computer Science, Machine Learning, Artificial Intelligence, Data Science, Computational Linguistics, or a closely related STEM field.
• Hands-on exposure to parameter-efficient fine-tuning methodologies, specifically configuring model adapters via **LoRA (Low-Rank Adaptation)**.
• Practical exposure to cloud-based model serving infrastructure or real-time model telemetry and drift tracking setups.
• A disciplined approach to software craft, including writing test-driven code configurations and maintaining clear, rigorous experiment documentations.

What We Offer

• The exceptional professional canvas to directly direct, code, and deploy the natural language understanding models processing customer feedback for the world’s most prominent technology brands.
• Highly competitive, capability-calibrated compensation structures supplemented by immediate participation in the company’s milestone equity options scheme.
• Profound work-from-home remote parameters offering supreme lifestyle flexibility, a dedicated remote workspace allowance, and full scheduling trust under a choice-first framework.
• Generous time-off benefits comprising 25 days of annual holiday (plus local bank holidays), an extra day off for each year of service, and your birthday off.
• Access to a dedicated annual personal Learning and Development budget to fund advanced machine learning research papers, AI conventions, and technical books.
• Comprehensive health and wellbeing budget monthly allocations alongside optional private healthcare plans, life assurance, income protection lines, and an Employee Assistance Programme.
• Enhanced corporate family leave provisions, incorporating advanced fertility and neonatal leave care protections.
• Access to a dog-friendly physical office hub in London featuring rooftop terraces, fully supported team classes, and collaborative networking events.