Top Data Science Jobs in Bristol

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.

Drive discovery and development of data and AI products, translating business problems into solution hypotheses. Manage stakeholder priorities, product roadmaps, and strategies while aligning outcomes with business goals. Define and measure product value throughout the lifecycle, promote data-led decision-making, and collaborate cross-functionally to drive adoption and delivery.

Drive discovery and development of data and AI solutions, translate business problems into product hypotheses, manage stakeholder priorities, align roadmaps with business goals, define and measure product outcomes, communicate value, and promote data-led decision-making and adoption across teams.

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.

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.

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.

Lead digital delivery and optimization across AECOM’s England and Wales water operations. Develop digital strategies, advise clients on transformation, data governance, operating models, and platform adoption, and identify AI, automation, and data science opportunities. Lead digital workplans, client workshops, stakeholder engagement, bid responses, and regional team adoption of digital solutions. Partner with account managers and delivery teams to build opportunities and deliver measurable outcomes across complex infrastructure programs.

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.

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.

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.

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.

Develop statistical and machine learning solutions for customer and energy-transition challenges, from problem discovery and experimentation through prototype validation and production handover. Lead end-to-end analytical workstreams, collaborate with customers, engineers, domain experts, and product teams, and mentor data scientists. Build models for time-series and text data using Python and data science libraries, working with databases, APIs, pipelines, Kubernetes, Linux, Git, and Docker.

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.

Supports Flight Physics data science projects focused on data analytics, visualization, and machine learning. Develops customizable visualization frameworks using a three-tier web application architecture, analyzes static and dynamic Flight Physics datasets, and contributes to innovation projects that enable strategic transformation. The placement also provides exposure to additional technical topics, software development, and emerging technologies.

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.

Provide technical leadership for solution design and assurance across pre-sales and delivery. Translate ambiguous customer needs into costed, deliverable architectures for sensing, AI, communications and edge environments; assess hosting, integration and platform options; manage technical risks; produce bid and governance artefacts; engage stakeholders and support contract mobilisation to ensure coherent end-to-end delivery.