Top Data Science Jobs in Edinburgh

Own enterprise customer programs from contract signature through expansion, leading delivery teams, milestones, stakeholder communication, adoption, and change management. Partner with sales and customer success to scope engagements, identify expansion opportunities, and translate executive goals into executable AI implementation plans. Serve as the customer advocate internally while guiding solutioning across model development, deployment, governance, and enterprise data science workflows.

As the Director of Data Science, you'll mentor teams, oversee projects, drive data-driven decisions, and implement AI and ML solutions while enhancing our data pipeline.

Lead the transformation of legacy products into a unified enterprise platform. Translate strategy into roadmaps, manage backlogs, prioritize cross-functional initiatives, and coordinate Engineering, UX, AI, Data Science, Commercial, and Operations teams. Drive platform discovery, delivery, launch, adoption, and measurable business outcomes. Integrate trustworthy AI and data capabilities into customer-facing workflows while influencing senior stakeholders and balancing customer value, commercial goals, technical feasibility, risk, and resources.

Leads digital delivery and optimization across AECOM’s Scottish water projects and frameworks. Develops digital strategies, governance models, operating approaches, platform roadmaps, and measurable workplans. Advises clients, facilitates stakeholder workshops, identifies automation and AI opportunities, supports MVP development, and promotes adoption of digital tools. The role also manages regional capability development, resource allocation, client opportunities, and digital-focused bids and tenders.

Develops Gartner research and thought leadership on the economic impact of AI and technology disruption. Synthesizes economic analysis, quantitative evidence, financial statements, market intelligence, and business context into executive-level insights. Advises clients, presents at conferences and media engagements, supports business development, reviews research, and collaborates with modeling, data science, and data engineering teams. The role also contributes to research strategy, mentors colleagues, and builds authority in technology market economics.

Lead and mentor a data science team developing machine learning systems for threat detection and agentic AI. Set ML technical strategy, standards, roadmaps, and deployment practices; guide projects from research through production; collaborate with security, engineering, and product teams; develop advanced malware and behavioral threat models; communicate insights; and contribute to research, publications, patents, and hands-on technical work.

Leads the FCA’s Agentic AI and Data Science Research function, setting AI strategy, governance, research ethics, data science standards, and long-term capability roadmaps. The role directs horizon scanning, responsible AI adoption, model assurance, and advanced analytics initiatives supporting regulation, financial crime reduction, and organisational effectiveness. It provides senior technical advice, leads multidisciplinary teams, develops talent, and influences executive, board, regulatory, and technology stakeholders.

Leads a 25+ person organization of data scientists, machine learning engineers, and analytics engineers across Identity and Financial Crime. Owns data quality, governance, lineage, observability, fraud and financial-crime models, production performance, monitoring, retraining, and domain data products. Partners with engineering, product, risk, compliance, legal, and central data teams; influences upstream teams, develops managers and senior ICs, handles incidents, and scales hiring and technical strategy.

Lead technical discovery, solution design, demonstrations, and proof-of-concept support for Anaconda’s AI and data science platform across EMEA. Partner with account executives on complex deals, create reusable technical content, represent customer needs to product and engineering, and coordinate with cross-functional teams through implementation handoff. Manage multiple opportunities independently while improving technical win rates, deal expansion, sales velocity, and regional pipeline development.

As a Senior Data Science Engineer, you'll lead data science projects, develop algorithms, analyze datasets, and mentor junior team members to enhance trading operations and strategies.

Develop and scale NVIDIA Inception’s European startup ecosystem by identifying, technically assessing, recruiting, enabling, and nurturing AI and accelerated-computing startups. The role advises founders and technical leaders on CUDA, NVIDIA SDKs, AI frameworks, GPU infrastructure, and platform adoption; leads technical workshops; translates ecosystem feedback into product insights; collaborates with venture capital firms and internal teams; and supports sales and enterprise customer motions. Travel across Europe is required approximately 40% of the time.

Build Paddle’s data science function and production decisioning systems from the ground up. Prioritize high-value use cases, personally deliver the first ML or agentic system, and own deployment, monitoring, experimentation, reliability, governance, and financial impact. The role will establish the production ML stack, collaborate across Product, Engineering, Risk, Finance, and Compliance, then hire and lead data scientists and ML engineers. Experience with regulated transactional domains, production ML operations, experimentation, and executive stakeholder management is required.

Lead and mentor a data science team building ML and LLM solutions for cybersecurity. Translate business needs into research and production ML objectives, prioritize roadmaps, collaborate cross-functionally, and drive technical vision, model development, and operationalization for malware detection and threat analysis.

This role invites speculative applications for various tech positions. Candidates with skills in Salesforce, DevOps, AWS, and user experience are encouraged to apply.

Leads the Payments data strategy and partners with Product, Engineering, and Design to shape payment products, commercial optimization, customer growth, metrics, architecture, and operating models. Builds and scales a high-performing, full-stack data organization spanning data science, analytics engineering, machine learning engineering, and analytics. Serves as a trusted Payments Leadership partner, translating technical, product, and commercial perspectives into high-impact decisions.

Leads and develops a team of Data Scientists and other Data professionals, setting strategic direction and identifying high-impact opportunities. Partners with Product, Engineering, and senior stakeholders to shape product strategy and influence decisions through experimentation, causal inference, statistical modelling, machine learning, and analytics. Ensures analytical work drives measurable customer and commercial outcomes while collaborating with other data disciplines on tooling and infrastructure. Also contributes to hiring, coaching, technical standards, and the broader Data Science practice.

Lead a financial crime data science team focused on detecting, preventing, and mitigating financial crime. Partner with Product, Risk, Engineering, and control owners to shape data strategy, generate strategic insights, improve product decisions, and deliver rigorous analytics and machine learning solutions. Hire, develop, and retain data scientists and analysts while supporting innovation through business intelligence, experimentation, causal inference, and self-serve analytics.

The Senior AI Transformation Consultant works with clients to identify AI opportunities, define robust business cases, and oversee AI project deployments, ensuring solutions deliver value.

Manage curriculum development for data science and engineering, collaborate with instructors, create content, and drive improvements based on learner feedback.

As a Curriculum Manager, you will manage content development for the data science and engineering curriculum, collaborating with instructors and teams to enhance learning experiences.

Lead and grow a data science team to design, develop, evaluate, and deploy production-grade AI/ML solutions (LLMs, Generative AI, RAG, transformers). Own technical vision, MLOps/LLMOps, model governance, and cross-functional execution with Product and Engineering to deliver scalable business impact in financial markets.

As a Curriculum Manager, you will manage the content development lifecycle, collaborate with instructors, and improve data science curriculum, ensuring technical accuracy and pedagogical effectiveness.

The Curriculum Manager will oversee the content development lifecycle, recruit instructors, design curriculum, assess course performance, and improve data science and engineering content.