Top Data Science Jobs in Edinburgh

Manage the EMEA Security Operations Center within a global 24/7 operation. Responsibilities include defining processes, workflows, and playbooks; maintaining shift coverage and quality assurance; coaching analysts; developing training; partnering with Product, Support, and security teams; improving incident response capabilities; tracking objectives and key results; operationalizing new services; and representing the company in public speaking engagements.

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.

Own and scale global paid acquisition across WorldRemit and Sendwave, managing multi-million-pound budgets and a team of five. Set channel strategy, optimize customer acquisition and revenue performance, lead experimentation, oversee attribution and measurement, and identify growth opportunities. Partner with Product, CRM, Data Science, Brand, Finance, Legal, and agencies to improve CAC, ROAS, LTV:CAC, and campaign effectiveness across markets.

Adjudicate automated vessel detections humans cant resolve: identify dark/spoofed/low-confidence contacts, investigate AIS/GNSS manipulation and ownership, produce sourced identification records, and supply labeled ground truth to improve detection models.

Leads flagship AI Labs initiatives from scoping and research through production deployment. Designs and evaluates AI agents and agentic workflows, guides production-grade architecture, establishes quality and safety measurement, and partners with business and engineering stakeholders. Manages and mentors 3–6 AI scientists while communicating technical outcomes to senior leaders and broader audiences.

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.

Lead and develop a Data Science team to deliver scalable ML/AI solutions for an online Personalisation programme, ensuring impactful customer experiences.

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.

Manage and grow relationships with Western Europe e-commerce clients as a trusted advisor. Ensure CDP delivers measurable value, align platform with client strategy, drive adoption, advise on analytics and marketing best practices, and balance client and Bloomreach objectives to create win-win outcomes.

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.

The Head of Data Ops and Systems leads technology infrastructure and data capabilities, ensuring systems are reliable and secure while overseeing data management and compliance.

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.

Own and prioritise the platform product backlog, work with remote engineering to refine stories and unblock delivery, shape roadmap with leadership, gather and validate requirements with stakeholders/customers, write user stories and acceptance criteria, and balance features, technical debt and operational stability while understanding APIs, data models and integrations.

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.

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.

Designs, builds, and maintains scalable data pipelines supporting data science and advanced analytics. Manages reliable Airflow orchestration, delivers data engineering solutions using Databricks, and contributes to GitHub-based collaborative development, code reviews, and engineering standards. Partners with data scientists, supports controlled feature-led delivery, investigates root causes, and develops practical solutions. The role also values adaptability, continuous learning, and exposure to MLOps concepts and tooling.

Designs, builds, and maintains scalable data pipelines supporting data science and advanced analytics. Manages Airflow orchestration and delivers data engineering solutions using Databricks. Collaborates through GitHub, code reviews, and shared engineering standards in feature-led environments. Partners with data scientists, owns delivery outcomes, performs root-cause analysis, and continuously improves pipeline reliability, observability, and maintainability. Exposure to MLOps concepts and tooling is desirable.

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.

Lead and grow a Data Science team to deliver end-to-end, scalable ML/AI solutions for online personalisation. Partner with product, engineering and commercial teams to embed models, set standards for agile delivery, testing and model monitoring, and drive innovation to improve customer experiences and business 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.