Senior AI Scientist

Mental Health Innovations

. Investigate open questions about MHI’s services and the people who use them, designing studies that produce robust evidence with actionable reports.

Posted 11/5/2026full-timeLondon • United KingdomSenior💰 £55,000 - £75,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Machine Learning and Natural Language Processing, with a strong foundation in Statistics and Research Design. Capable of developing AI strategies and conducting rigorous evaluations while ensuring ethical considerations in handling sensitive data.

Highest-signal resume keywords

PhD In Quantitative FieldStrong Python SkillsMachine Learning And NLP ExperienceAI Governance KnowledgeExperience In AWS

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningNatural Language ProcessingStatistical AnalysisResearch DesignDeep Learning FrameworksSQLAI Model EvaluationData AnalysisTechnical PrototypingRisk Assessment

Soft Skills

Excellent CommunicationCollaboration SkillsProactive Problem SolvingMentoring AbilitySelf-Motivated

Tools & Technologies

AWSAmazon SageMakerAmazon BedrockPyTorchTensorFlowJAXHugging Face

Industry Keywords

Digital Mental HealthAI In HealthcareSocial Impact TechnologyAI EvaluationEthical AI

Tech Stack

Tools & technologies

AWSCloudPythonPyTorchSQLTensorflow

About the role

Key responsibilities & impact

Investigate open questions about MHI’s services and the people who use them, designing studies that produce robust evidence with actionable reports.
Apply ML and NLP methods to large volumes of free-text data, including conversations from crisis, peer support and counselling services, with careful attention to validity, reliability and bias.
Build technical prototypes to test whether AI approaches are viable, and work with colleagues to take promising approaches forward.
Design and run rigorous evaluations of AI models and tools, validating automated methods against clinical expert judgement and conducting safety testing for high-risk conversations.
Assess risks including bias, privacy, safety and potential harm, and help develop appropriate safeguards.
Work with the Director of Data Science, AI & Research to develop MHI’s AI strategy and research priorities.
Help shape technical and methodological standards, support and mentor colleagues, and advise on AI capabilities, limitations, opportunities and risks.
Collaborate with clinical, service delivery and external partners; communicate complex ideas clearly to non-technical audiences; and contribute to reports, publications and presentations.
Work with anonymised text from more than 4 million Shout conversations and growing datasets from The Mix’s services in a secure AWS environment using Amazon SageMaker and Amazon Bedrock.

Requirements

What you’ll need

A PhD or equivalent experience in a quantitative field, such as computer science, machine learning, statistics, physics, computational neuroscience or quantitative psychology, and a track record of high-quality, well-tested and reproducible technical work you have delivered yourself.
Strong Python skills, including proficiency with modern deep learning frameworks (e.g., PyTorch, TensorFlow, JAX, Hugging Face), and working knowledge of SQL for querying data.
Hands-on experience applying machine learning and NLP, including large language models, to real-world free text, and turning the results into clear, practical findings.
A strong grounding in statistics and research design, and experience designing and running evaluations of AI models or systems, including validation against human judgement.
Sound judgement about when AI is and is not the right approach, a preference for the simplest method that solves the problem, and an understanding of responsible AI, including fairness, transparency, privacy and safety.
Proactive and self-motivated, with the ability to take initiative, work independently and manage your own priorities, including spotting problems worth solving.
Excellent communication and collaboration skills, including explaining technical work to non-specialists and supporting or mentoring colleagues.
Ability to handle sensitive mental health data with care, and a commitment to using technology ethically to create positive social impact.
Experience applying AI in mental health, healthcare, or other social and public-interest settings.
Knowledge of AI governance, assurance or risk management, including regulation relevant to AI in health.
A track record of publications or research reports in machine learning, NLP, AI evaluation or digital mental health.
Experience working in AWS or another cloud platform, including running machine learning workloads and using managed AI services.
Experience working with external research partners or managing collaborative projects.
Experience translating research into practical tools, recommendations or policy.
Eligibility to work in the UK.
Satisfactory background and reference checks.
Visa sponsorship is not available.

Benefits

Comp & perks

25 days annual leave per year, plus public holidays
Company electronic devices
Enhanced salary sacrifice pension scheme
Private health insurance after completion of probation
Eligibility for a Blue Light discount card
EAP service that offers mental health support
Mental health first aiders that can provide confidential support
1 hour paid lunch break included in the 40-hour work week