Top Machine Learning Jobs in Edinburgh

CrowdStrike seeks a Senior Intelligence Analyst to provide threat intelligence and digital risk monitoring, collaborating with teams to deliver customer-focused solutions and presentations, while maintaining customer relationships.

As a Product Manager at Bringg, you will define product strategy, work with stakeholders, manage the roadmap, and integrate AI into logistics solutions.

Provide clinical guidance across sales, implementation, product, and support teams for InterSystems health information solutions. Engage senior clinical and executive stakeholders, lead demonstrations and workshops, support procurement and digital transformation, and translate clinical requirements into solution narratives to drive adoption and product strategy.

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.

Lead and manage an ML engineering team building post-origination credit models for repayment, collections, recovery, and loss mitigation. Define technical strategy, design and scale ML solutions, partner with product, engineering and risk, mentor engineers, and operationalize models to minimize loan loss and personalize collections.

Lead the creation of user-centric digital products in financial services, focusing on intuitive design and leveraging AI for enhanced user experiences.

Build and maintain high-performance ETL pipelines for trading data, create interactive dashboards and web apps, apply machine learning to market data, deploy scalable cloud solutions, and provide analysis to support supervisory and policy decisions across equities, fixed income, commodities, and FX.

As a C++ Engineer, you will develop machine learning features, integrate models, maintain SDKs, and collaborate across teams for software performance and enhancements.

Lead and deliver statistical support for Phase II-III clinical trials embedded with a sponsor: design input, SAP/sample size, interim/final analyses, oversight of programmers/statisticians, regulatory submissions, and collaborate cross-functionally to ensure compliant, high-quality statistical deliverables. Apply advanced statistical methods and ML/DL for analytics and process automation.

Drive data-informed capital allocation by building financial models (NPV, IRR), applying AI/ML for forecasting and scenario planning, creating build-vs-buy and prioritization frameworks, implementing decision-support systems, collaborating with cross-functional stakeholders, and monitoring post-investment performance to refine allocation models.

Design, implement, and monitor AI/ML models to improve underwriting risk assessment, pricing, and portfolio management. Translate underwriting rules into data models, integrate models into workflows, analyze datasets for risk patterns, build decision-support tools, ensure compliance and fairness, and collaborate with underwriting, actuarial, product, and engineering teams.

Design, implement, and optimize AI-powered solutions to support financial compliance and controls. Monitor GAAP/IFRS adherence, automate controls and reporting, support internal/external audits, and manage complex accounting areas like revenue recognition and lease accounting while collaborating with finance, audit, and technology teams.

Contract role combining actuarial science, risk management, and AI to improve portfolio performance. Responsibilities include loss and combined ratio analysis, portfolio risk assessment, catastrophe and exposure modeling, stress testing, and integrating ML to enhance pricing, reserving, and risk selection while collaborating with underwriting, finance, and product teams.

The Data Scientist will analyze data, build and refine machine learning models, document technical designs, and collaborate with multidisciplinary teams to deliver AI solutions.

The role involves building infrastructure for training open source foundation models, with emphasis on autonomy and contributing in a dynamic team.

Lead clinical studies by providing statistical support, employing advanced analytical methods, and collaborating with cross-functional teams to optimize clinical development processes.

The Senior FinCrime Product Owner will design and implement a financial crime prevention product, develop strategy, and lead product delivery at Deblock.

The Customer Value Architect will engage with customers to ensure the effective adoption and value realization of the Neara platform, focusing on ROI metrics and customer relationships.

The Customer Success Manager will onboard and support Portuguese utility accounts, ensuring effective use of digital twin technology and driving long-term partnerships and customer satisfaction.

Drive independent, high-impact research on frontier AI topics, publish findings, collaborate widely, and mentor new researchers in the field.

The role involves designing, building, and deploying ML systems, supporting stakeholders, and operationalizing AI applications in Defence.

The Executive Partner manages a portfolio of clients, providing expert guidance in Data & Analytics, mentoring executives, and ensuring client value through various engagements. Responsible for retention and growth, the role emphasizes collaboration with internal teams and requires strong executive presence.

Lead cross-functional teams of machine learning engineers and data scientists, driving technical direction and fostering a collaborative environment to develop high-quality ML-driven capabilities.

The Director of Data & Analytics will lead financial crimes advisory engagements, mentor teams, ensure quality deliverables, identify business opportunities, and develop strategic relationships while managing client expectations and risks.

Lead engineering systems and teams for an AI chat application, focusing on backend, mobile, and desktop. Oversee strategy, architecture, integration, and high-impact technical decisions for reliable user experiences.