Top Data Science Jobs in Manchester

Leads strategic R&D engagements from presales through delivery, translating scientific and business challenges into AI architectures, product backlogs, MVPs, simulations, integrations, data pipelines, and production solutions. Builds trusted relationships with R&D executives, scientists, engineers, and technical teams; assesses data, compute, feasibility, value, staffing, and delivery plans. Develops reusable architectures and playbooks, oversees technical workstreams, evaluates emerging AI capabilities, and provides feedback to shape Microsoft Discovery products and scalable industry solutions.

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 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.

Leads digital delivery and optimisation across AECOM’s England and Wales water operations. Develops digital strategies, advises clients on transformation, data governance, platforms and roadmaps, and champions AI, machine learning and data science adoption. Identifies automation opportunities, supports MVP development, manages regional enablement, contributes to bids, and facilitates client workshops and stakeholder presentations. The role requires strong digital expertise, infrastructure or water-sector experience, and the ability to influence technical and non-technical stakeholders.

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 automation strategy for global VAT compliance and reporting. Identifies process inefficiencies, translates VAT requirements into technical solutions, manages automation projects through implementation, and supports ongoing process improvements. Works with clients, VAT teams, delivery groups, and technology teams while applying analytics, data science, AI, workflow automation, and emerging technologies. Also coaches team members, manages delivery risks, ensures data integrity and controls, and prioritizes initiatives independently.

Lead enterprise architecture consulting engagements by aligning technology strategy with business goals, developing architecture frameworks, capability models, operating models, and transformation roadmaps. Advise senior client stakeholders, support sales and proposals, govern solution delivery, mentor teams, and build internal architecture methodologies and offerings. The role spans business, data, application, technology, infrastructure, cloud, emerging technologies, security, and enterprise transformation.

Participate in a 24-month rotational engineering analyst program focused on data science. Apply data analysis, profiling, feature engineering, statistical methods, and machine learning to solve business and engineering problems. Build scalable analytical processes, models, and tools using Python, JavaScript, Java, CSS, and related technologies. Collaborate with engineering and business teams to translate data insights into practical recommendations and improve decision-making.

Design and develop AI solutions for complex problems, integrating AI capabilities into systems and improving effectiveness through experimentation and evaluation.

Develop and evaluate AI/ML and Generative AI/LLM models from POC to production, perform data science and statistical analyses to support business decisions, document and assess model risk, publish patents/papers, collaborate with SMEs, and provide technical leadership while deploying solutions with modern Agile/DevOps and cloud practices.

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 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.

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.

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.

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.

Senior pricing and analytics leader for Asset Servicing responsible for developing pricing frameworks, governance, and margin management. Translate analytics into commercial insights, collaborate with product teams on benchmarks and fee schedules, maintain KPIs, and modernize BAU with AI, data science, automation and MLOps. Lead stakeholders and drive accountability for business outcomes.

Participate in a 10-week data science engineering internship by applying analytical methods to business and engineering problems. Analyze and profile data, perform feature engineering, identify patterns and anomalies, and build automated models and analytical tools. Collaborate with engineering and business teams to translate insights into recommendations and scalable data-driven solutions. Gain experience in programming, advanced analytics, machine learning, distributed computing, and communicating complex results.