22 of 22 Permanent Benchmarking Jobs in Slough

Design, execute, and analyze A/B and multivariate tests across the user journey. Own experiment setup and post-test performance reporting to validate hypotheses and inform optimization. Market Benchmarking & Competitive Insights: Assist with competitive research and tracking key metrics (e.g. pricing, UX, product feature, positioning) of top players in cross-border payments, helping inform Xe’s go-to-market More ❯

modeling, including MMM, attribution and unified measurement, testing, segmentation, behavioral sciences, choice analytics, simulation, war gaming, and forecasting. High-touch consultancy that includes bespoke roadmaps, training and education, industry benchmarking, and activation planning. At Gain Theory, we love accelerating growth for ambitious brands and people. As a Gain Theorist, you will need to demonstrate behaviors that support our values. Our More ❯

cycle on an independent and proactive basis. Inform procurement, value, and financial management activities. Identify, make and/or escalate legal and strategic decisions as appropriate. Develop internal cost benchmarking of construction prime costs, fees, cashflows, inflation and other data points necessary to the development of business cases. Supervise cost consultant teams, including developing their appointments, setting to work and More ❯

Insights Act as the voice of the customer synthesising insights from customer feedback, usage data, and market research to inform positioning and roadmap priorities. Conduct market, competitive, and pricing benchmarking to identify opportunities for differentiation and growth. Test and validate new product concepts (including the enterprise solution) to assess market need, feature relevance, and commercial potential. Develop proof points, customer More ❯

feature engineering, model development, validation, monitoring, and iteration. • Tooling & Workflow Analysis: Review the ecosystem of analytical tools, frameworks, and environments used for data science, including reproducibility and collaboration readiness. • Benchmarking: Define benchmarks for best practices in experimentation, automation, and applied machine learning operations (MLOps). • Collaboration & Alignment: Work with AI and Data & AI Architects to connect findings from people, platform More ❯

feature engineering, model development, validation, monitoring, and iteration. • Tooling & Workflow Analysis: Review the ecosystem of analytical tools, frameworks, and environments used for data science, including reproducibility and collaboration readiness. • Benchmarking: Define benchmarks for best practices in experimentation, automation, and applied machine learning operations (MLOps). • Collaboration & Alignment: Work with AI and Data & AI Architects to connect findings from people, platform More ❯

and deployment of AI/ML powered applications – especially using language models or NLP and agent-based approaches (e.g. LangGraph, PydanticAI, AutoGen) Knowledge of AI/ML evaluation and benchmarking approaches, experience with iterative improvement of AI/ML models and products Some experience with frontend software development (e.g. React More ❯

partnerships Experience working within markets with an understanding of regional differences in regulation and business culture Strong growth and metrics fluency, including funnel optimization, retention analysis, and partnership performance benchmarking Technical understanding sufficient to engage with product and infrastructure teams on feasibility assessments Financial Markets Knowledge: Understanding of financial instruments, market structure, and regulatory frameworks Familiarity with tokenization trends and More ❯

and deployment of AI/ML powered applications – especially using language models or NLP and agent-based approaches (e.g. LangGraph, PydanticAI, AutoGen), Knowledge of AI/ML evaluation and benchmarking approaches, experience with iterative improvement of AI/ML models and products. Research experience (e.g., Master’s project, internship at research organization). Cloud experience (e.g. Google Cloud and cloud More ❯

Package : Highly competitive base + benefits What You’ll Do Design, build, and maintain high-performance Java applications used in demanding real-time systems. Develop and enhance testing and benchmarking frameworks to validate system performance. Identify and eliminate bottlenecks through systematic performance analysis . Contribute ideas and innovations to improve architecture and speed. Quantify and document measurable performance improvements. Requirements More ❯

computer science...) Expertise in machine learning, with a strong understanding of flow matching, diffusion and/or GANs Machine learning orientated programmed skills (Pytorch, Python...) Experience in developing and benchmarking new machine learning models Working with multi-GPU models Industrial experience in machine learning applications for either chemistry or biology settings Experience working in front of and with customers Previous More ❯

operations. Engage senior business sponsors and C-suite stakeholders , translating complex architecture into business outcomes and total-cost-of-ownership advantages. Champion data-driven decisioning across investment management, using benchmarking and insights to accelerate adoption. Drive SaaS and cloud transformation , shaping roadmaps that unlock economies of scale and enable future AI/ML-driven capabilities. Mentor cross-functional teams on More ❯

with AI/ML technologies such as LLMs, NLP, LangGraph, PydanticAI, or AutoGen Experience with biological or scientific datasets (genomics, proteomics, etc.) Exposure to frontend development (React preferred) Experience benchmarking and improving AI/ML models or agent-based systems What You'll Bring A track record of delivering clean, production-grade backend systems A collaborative and proactive approach to More ❯

Advance Large Vision Models (LVM) — Improve performance, scalability, and adaptability of our in-house LVM for diverse retail use cases. Deliver Proven Solutions — Experiment rapidly using PyTorch. Contribute to benchmarking and ongoing improvements. Collaborate Across Teams — Work with Product, Infrastructure, and Customer teams to integrate models into workflows. Provide technical leadership aligned with business goals. Champion Data & MLOps — Maintain high More ❯

using language models or NLP and agent-based approaches (e.g. LangGraph, PydanticAI, AutoGen). Prior experience conducting user research for AI applications. Knowledge of AI/ML evaluation and benchmarking approaches, including safety and robustness evaluations. Web-based front end development experience. Why GSK? Uniting science, technology and talent to get ahead of disease together. GSK is a global biopharma More ❯

organisations make evidence-based strategic decisions. With over five decades of research heritage in identifying the drivers of profitability and sustainable growth, the firm applies advanced analytical tools and benchmarking frameworks to deliver measurable performance improvement for clients across sectors including energy, manufacturing, financial services, and technology. Their mission is simple: to replace assumption with analysis — helping leaders make better … will work alongside experienced consultants and data scientists on projects that analyse company performance and identify the key drivers of strategic and operational success. You’ll apply quantitative methods, benchmarking models, and analytical frameworks to guide business improvement and support senior decision-making. This is the ideal role for someone who enjoys analytical problem-solving, working with data, and applying … bonus. 38 days holiday Private Healthcare & Dental Hybrid working model based in South West London . Direct exposure to senior consultants and data scientists. Hands-on experience in analytics, benchmarking, and strategic consulting. Supportive and intellectually stimulating environment. Clear progression and professional development opportunities. How to Apply This position is ideal for a 2024 or 2025 STEM graduate who is More ❯

each migration wave meets defined readiness criteria before production deployment. Lead System Integration Testing (SIT) and support UAT execution with business and application owners. Validate application performance through latency benchmarking and throughput testing. Manage the full defect lifecycle through Jira/Confluence or equivalent tools. 3. Quality Assurance & Risk Control Identify and mitigate risks related to test environment readiness, data More ❯

and deploy GPU-accelerated software and AI models at scale. Responsibilities: Design and maintain CI/CD pipelines for GPU-accelerated codecs and AI/ML libraries. Automate performance benchmarking and regression testing across multiple GPUs and hardware targets. Manage containerised environments (Docker, Kubernetes) to deploy GPU and ML workloads at scale. Provision and optimise GPU cloud infrastructure (AWS, GCP More ❯

based questions to assess AI understanding, solution design ability, and architectural thinking. • Talent Assessment: Evaluate existing AI talent through structured interviews, workshops, and scorecards to determine readiness and fit. • Benchmarking: Define what “best-in-class” technical architecture looks like within the context of large enterprise AI adoption, referencing current industry practices. • Cross-Functional Collaboration: Partner with program leads and consulting More ❯

FlameGraphs . Deep knowledge of NUMA-aware design , memory fences, and lock-free concurrency. Expertise in custom allocator design , branchless algorithms , and profile-guided optimization . A habit of benchmarking rather than assuming — data, not theory. Ideal Background Proven experience building ultra-low-latency systems in trading, gaming, or networking. Deep understanding of CPU architecture , from cache hierarchies to speculative More ❯

Senior Product Designer - £80,000 - Data & Analytics - London A leading data and analytics organisation is seeking a Senior Product Designer to help shape the next generation of data-driven insights products. This role offers the opportunity to transform complex data More ❯

multidisciplinary teams across software, hardware and research. You’ll play a key role in developing and refining new ML architectures, designing input/output encoding methods, and conducting rigorous benchmarking to evaluate and improve performance. This role is ideal for an engineer with a strong foundation in ML who enjoys both conceptual design and hands-on model development. Responsibilities Design … and test hybrid physical/software ML models tailored to next-generation computing platforms. Design and evaluate data encoding, preprocessing and postprocessing methods. Build tools and pipelines for performance benchmarking and model evaluation. Research and adapt state-of-the-art ML and computer vision techniques to new hardware paradigms. Collaborate cross-functionally with hardware, software and research teams. Requirements Strong More ❯