Dyad AI

Dyad AI is seeking a Data Scientist to enhance analytical capabilities. The role requires expertise in data extraction, analysis, and visualization with a strong emphasis on Python and SQL. Responsibilities include building dashboards, producing accurate reports, and effectively communicating findings to stakeholders. Applicants should have at least three years of experience in a commercial environment, ideally with a background in ML or AI. The position is offered on a hybrid basis from the London office.

Dyad is seeking a Data Scientist to help grow our analytical capabilities across our teams. This role fits someone who can pull, interrogate, and shape data from across the company, document the evaluations and benchmarks that matter to our AI Platform team and to Commercial, and turn all of it into dashboards, reports, and presentations that other people can act on. The role priorities end of the data science spectrum. It prioritises fluency with Python, SQL, and visualisation; clear reasoning about data quality and measurement; and communicating complex findings to stakeholders across the business. Communication fluency is a first class requirement: a correct analysis that stakeholders cannot act on is a failure of the role, not of the audience. You will work across Commercial, AI Platform, and BetterLetter, reporting into the Chief Clinical Product Officer. This role is offered on a hybrid basis from our London office. Core responsibilities Data extraction and analysis Work with BetterLetter, AI Platform, QARA, and Commercial to pull data from production systems, customer environments, and internal tooling. Clean, join, aggregate, and interrogate datasets with rigour in order to communicate findings to all stakeholders. Flag where data is missing, unreliable, or not yet instrumented to support the question being asked, and recommend what to do about it. Dashboarding and reporting Build and maintain dashboards for internal teams (product, commercial, leadership) and, where appropriate, customers. Produce recurring reports (customer facing metrics, operational KPIs, board packs and investor updates as that becomes necessary) that are accurate, legible, and consistent over time. Run bespoke analyses to support sales, renewals, clinical conversations, and strategic decisions. Present findings clearly to non technical audiences, including senior leadership and customers. Benchmarks and evaluations Turn benchmark and evaluation outputs produced by the AI Platform team into documentation, reports, and visualisations that other teams can use. Communicate technical evaluation metrics in understandable ways, and describe how evaluation results change over time in terms non specialists can act on. Requirements Experience and background A track record of applied data analysis work in a commercial setting is a must, with at least 3 years of experience; this is not a graduate role. We are seeking candidates with experience pulling, cleaning, and analysing data from production systems along with reporting and data visualisation. You should also be comfortable presenting findings to non technical stakeholders, including senior leadership or customers. Experience working in or alongside teams building data intensive products, ideally including ML or AI systems, is highly desirable. You might be trained as a data scientist with a preference for data work and strong applied data and statistical skills, or come from an analyst background but with sufficient fluency in writing Python to build and own reporting and analyses independently. Healthcare experience is a plus but not required. Technical skills Python for data work: pandas, NumPy, Jupyter, plotting libraries (matplotlib, Plotly, seaborn), and enough general Python to write small tools and scripts without help. SQL across common dialects, including reading and reasoning about non trivial queries and joins. A modern BI or dashboarding stack (Metabase, Looker, Superset, or equivalent), sufficient to build and maintain dashboards without engineering help for most work. Basic statistical thinking: sampling, confidence, effect sizes, and distinguishing a meaningful difference from noise. Reading and interpreting evaluation outputs from AI systems: precision and recall, error taxonomies, and what model metrics mean for a non specialist audience. Personal attributes Communication led: treats clear presentation as part of the analysis, not an afterthought. Pragmatic and outcome focused, willing to own the analytical question end to end. Comfortable flagging data quality issues early and shaping the question rather than only answering it. Cross functional by instinct: works effectively across engineering, AI, commercial, and clinical colleagues.

Dyad is seeking an NLP Engineer to join our Applied AI team and work on the clinical document understanding pipeline that underpins BetterLetter and related products. This is a hands on engineering role focused on building, improving, and maintaining production NLP systems. You will work on OCR aware document processing, entity extraction and linking, and the safe integration of LLM components within a constrained, regulated architecture. The role is offered on a hybrid basis from our London office. Core responsibilities Design, build, and maintain NLP pipelines for clinical document processing using Python. Develop and extend pipeline components as well as training configurations, packaging, and versioning. Refactor and improve pipeline components for maintainability, scalability, and clarity. Train, evaluate, and deploy NLP and OCR models for clinical concepts. Maintain evaluation datasets and implement regression testing for model and pipeline updates. Improve document structure detection, sectioning, and layout aware extraction, particularly for scanned documents. Enhance handling of negation, temporality, and related concepts in clinical text. Analyse production errors and implement targeted improvements to reduce recurring extraction and coding issues. Integrate LLM based components into the pipeline using structured inputs and validated outputs. This includes implementing schema validation, rule based checks, and other guardrails around model outputs. Optimise pipeline performance, including latency, throughput, and cost per document. Collaborate with Engineering to support production deployment and monitoring of NLP components. Requirements Minimum of a bachelor's degree in computer science, computational linguistics, or equivalent educational attainment. At least 2 years of commercial experience. This is not a graduate role. Strong professional experience in applied NLP and machine learning engineering. Advanced Python skills, including experience building and maintaining production ML systems. Hands on experience with common NLP frameworks. Experience training and evaluating NER and/or entity linking models. Experience working with noisy or unstructured text data, such as OCR derived documents. Familiarity with combining rule based and statistical approaches in production systems. Experience designing and implementing evaluation metrics and benchmarks as well as regression testing for NLP systems. Experience working with healthcare or clinical text. Familiarity with clinical terminologies such as SNOMED CT. Experience integrating LLMs into structured application pipelines. Experience working in regulated or high assurance environments. Exposure to hybrid symbolic and generative AI architectures. Personal attributes Detail oriented with a strong focus on accuracy and reliability. Pragmatic approach to problem solving, selecting appropriate techniques for the task. Comfortable working in a fast paced startup environment. Strong communication skills and ability to work effectively within a multidisciplinary team. Benefits Company pension. 25 days of paid annual leave (pro rata). Flexible hybrid working environment. Employee Assistance Programme. Modern, dog friendly office near Chancery Lane with free drinks.

A cutting-edge AI company is seeking an experienced NLP Engineer to join their Applied AI team in London. This role involves designing and maintaining NLP pipelines for clinical document processing, training and evaluating models, and integrating LLM components into production systems. The position offers a hybrid working environment, 25 days of paid leave, a company pension, and a modern office with flexible amenities. A strong background in NLP and Python is essential for success in this role.

Dyad is seeking a Head of Regulatory to own and operationalise our regulatory and compliance system as a core part of how we build products. This is a senior, working leadership role responsible for ensuring that medical device, quality, safety, and information security standards are embedded into day to day product and engineering workflows. The role is designed to build durable internal regulatory capability and position regulatory excellence, data protection, and clinical safety as a competitive differentiator rather than a cost centre. This role includes line management responsibility from day one and is offered on a hybrid basis from our London office. Regulatory system ownership Design, operate, and continuously improve Dyad's compliance framework across: Software lifecycle compliance Clinical safety integration Information security and data protection Ensure compliance processes are usable, scalable, and integrated into product and engineering workflows. Maintain audit readiness as a default state across the entire company. Own preparation, execution and follow up for audits and certifications. Respond to external data protection inquiries and requests, and manage customer interactions around compliance. Work in conjunction with our CSO and DPO. Compliance as a design discipline Treat regulatory requirements as design constraints, not blockers. Proactively reduce friction in compliance heavy workflows. Innovate in how compliance is implemented, documented, and maintained, with a focus on making it easier and safer to ensure regulatory and compliance excellence. Educate teams so compliance becomes habitual and embedded rather than reactive. Cybersecurity, data protection & privacy Own operational implementation of cybersecurity standards as well as data protection and privacy by design across the business, including but not limited to: GDPR HIPAA DSPT ISO 27001 Lead DPIAs, privacy risk assessments, and vendor risk reviews. Coordinate incident response from a compliance perspective. Regulatory authority & representation Define and update internal regulatory processes and SOPs. Interpret and operationalise standards such as: ISO 13485 ISO 14971 ISO 62304 ISO 27001 Approve routine compliance decisions related to product development and release. Represent Dyad in routine interactions with auditors and certification bodies. Escalate high risk decisions and regulator facing matters to senior leadership as appropriate. Team leadership & capability building Manage and develop at least one direct report from day one. Coach junior regulatory staff and delegate effectively. Ensure regulatory knowledge is documented and transferable. Avoid creating new single points of failure within the compliance function. Requirements Regulatory & quality expertise Significant hands on experience operating medical device quality systems. Strong understanding of: ISO 62304 (software lifecycle) NHS clinical safety standards (e.g. DCB0129 / DCB0160) Experience integrating regulatory requirements into product development workflows. Information security & data protection Experience implementing or maintaining ISO 27001. Familiarity with SOC 2, HIPAA, GDPR, and NHS standards such as DTAC and DSPT. Experience leading DPIAs and privacy risk assessments. Practical understanding of privacy by design in technical environments. Experience managing regulatory teams or compliance functions in growing organisations. Comfortable operating as a hands on working leader. Able to balance rigour with pragmatism in fast moving product environments. Strong written and verbal communication skills, with the ability to explain complex regulatory concepts clearly to non specialists. Personal attributes Calm, credible and solutions oriented under delivery pressure. Collaborative partner to Product and Engineering rather than a gatekeeper. Pragmatic and systems focused rather than bureaucratic. Comfortable representing regulatory posture to customers, auditors, investors, and partners. Our hiring process Introductory screening interview (30 minutes) Interview with senior leadership and cross functional partners Final interview and offer Company pension 25 days of paid annual leave (pro rata) Flexible hybrid working environment Employee Assistance Programme Modern, dog friendly office near Chancery Lane with free drinks