Top Data Science Jobs in Belfast

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.

Sources and researches target accounts, conducts high-volume outbound prospecting through email, phone, social, and video, and generates qualified meetings for Account Executives. Engages senior contacts, communicates InfluxDB’s technical value, nurtures early-stage prospects, and converts interest into qualified leads. Requires German and English fluency, consultative sales experience, strong communication and organizational skills, technical aptitude, and familiarity with AI-enabled processes and sales tools.

Generate qualified sales meetings by researching target accounts, conducting high-volume outbound outreach through email, phone, social, and video, articulating InfluxDB’s value, and nurturing prospects into qualified leads. The role requires consultative sales ability, strong communication, organization, persistence, technical aptitude, and familiarity with AI-enabled processes. Experience with open-source or SaaS sales, Salesforce, Outreach, remote work, quota attainment, and German or French is advantageous.

Leads Ofcom’s research innovation and data strategy, overseeing statistics, analytics, behavioural research, innovative research methods, and programme management. The role develops responsible data and AI capabilities, improves access to insight, strengthens cross-organisational collaboration, manages senior teams and budgets, and represents Ofcom externally. It requires strategic leadership, advanced data science and research expertise, data ethics knowledge, programme management, change leadership, and the ability to communicate complex analysis to regulatory, policy, commercial, and external stakeholders.

Drive Dataroid’s UK enterprise sales expansion, primarily targeting banks and financial institutions. Build market presence, develop go-to-market plans, prospect proactively, manage qualified pipelines, engage senior decision-makers, secure executive meetings, and close new business. Collaborate with leadership, product, and technical teams to advance opportunities while providing market insights and customer feedback.

Develop data-driven solutions to complex real-world problems using data science, machine learning, statistical modeling, and analytical reasoning. Candidates should currently work in a technical data science or machine learning role at a leading technology company, hold a quantitative undergraduate degree from a top-ranked university, and reside and work in an eligible English-speaking country.

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.

Reconstructs and redesigns data-driven presentations in Microsoft PowerPoint, creating visualizations and analytics reports that communicate complex insights clearly. Reviews and edits content for accuracy, flow, and narrative impact; applies data analysis and statistical reasoning; and refines slides based on feedback. The role supports AI training projects through high-quality presentation and analytical deliverables.

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.

Manage Independent Data Monitoring Committee and endpoint adjudication projects for clinical trials. Responsibilities include planning schedules and budgets, coordinating innovation, data science, and technology teams, monitoring risks and progress, communicating with stakeholders, and supporting emerging technology integration. The role requires strong project management, organization, communication, and cross-functional collaboration skills, with endpoint adjudication experience preferred.

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.

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.