AI Data Science Consultant 7 months Primarily remote, with shared office space once per week (london). Occasional client meetings - max 1 day per week on-site. About the Company • London-based consulting firm • Small, highly specialised team of industry and subject matter experts • Focus areas: Uncrewed Aircraft Systems (UAS / drones) , Sustainable aviation, Advanced Air Mobility (AAM) • Vision: Empower the aviation industry to achieve a sustainable future - Through advanced technology, deep industry knowledge, and collaboration • Mission: Help aviation organisations deliver optimised, sustainable, and resilient solutions • Driven by a passion for innovation and impact in aviation • Secured funding for a regulatory innovation office, primarily focused on exploring how AI can be applied to drone policy development and implementation. • Around 95% of the work is in partnership with the CAA (Civil Aviation Authority). • The project is scheduled to start on 1st September and run until the end of March (7-month contract) Team • There's already a core team with strong policy and consulting experience, along with front-end developers on the user side. • They're working with external technical people on a consulting basis Project • Join a close-knit team working on Drone flight initiatives • Collaborating with: Central government, Regulators, Industry stakeholders • New project focus: Researching and prototyping AI-based tools, Supporting UAS policy development, Assisting operators in applying policy • Project aims to Shape the UK's approach to safe and efficient drone regulation • This is a discovery-phase role focused on exploring and prototyping AI applications in drone regulation. Project goals include: • Identifying where AI can support policy development • Building POCs and prototypes • Delivering a business case outlining various AI use cases and feasibility • Exploring use of NLP tools to process and interact with policy documents • Developing support tools like chatbots or interactive guidance systems Role Overview The candidate will work alongside a multidisciplinary team of aviation consultants, AI engineers, policy experts, and UX developers. The role involves: • Prototyping AI/NLP tools for policy analysis and consultation feedback processing • Building retrieval-augmented generation (RAG) systems to provide policy guidance • Preparing datasets and pipelines using structured and unstructured regulatory data • Contributing to model evaluation and iteration based on user feedback • Developing prototype tools to support operators, such as chatbots and evidence-checking features • Documenting technical processes and outcomes for R&D reporting Key Responsibilities • Identifying opportunities to apply AI techniques across the policy development lifecycle • Cleaning, transforming, and preparing data for AI models • Implementing and fine-tuning NLP models for tasks such as classification, clustering, and sentiment analysis • Assisting in the development and testing of AI features for internal proof-of-concept tools • Collaborating with the UX and front-end team to ensure output usability • Supporting model integration and testing under the guidance of the AI Engineer Ideal Candidate Profile • Not purely technical - someone with a management consultancymindset, able to handle ambiguity and blend strategy with delivery • MSc with some practical elements (recent grad or early career) • Strong communication and collaboration skills • Comfortable working independently and taking initiative • Flexibility in working across evolving priorities • Background in AI, NLP, or policy-related AI applications • A person with strong technical skills might see this as a short-term contract, whereas a more well-rounded candidate could fit longer-term needs. Desirable Skills • Familiarity with retrieval-augmented generation (RAG) architectures • Experience with front-end data visualisation • Understanding of UAS (drones), aviation, or other regulated industries • Involvement in agile software development environments • Strong communication skills, particularly the ability to explain technical ideas to non-technical audiences