[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"job-search-\u002Fen-gb\u002Fjobs-by-expertise\u002Fexperimentation":3,"seo-content-expertise-experimentation-gb":104,"expertise-filters-\u002Fen-gb\u002Fjobs-by-expertise\u002Fexperimentation":120,"featured-jobs-\u002Fen-gb\u002Fjobs-by-expertise\u002Fexperimentation":253},{"total":4,"jobs":5},2,[6,69],{"id":7,"slug":8,"title":9,"raw_title":10,"is_featured":11,"company":12,"raw_hiringOrganization_logo_url":10,"processed_city_gmaps":15,"processed_country_iso_code_gmaps":17,"processed_home_office":19,"processed_salary_min":20,"processed_salary_max":21,"processed_salary_currency":22,"processed_salary_source":23,"processed_working_hours":24,"processed_employment_types":26,"processed_it_skills":27,"processed_it_skills_labels":30,"processed_job_expertise_skills":46,"processed_job_expertise_skills_labels":47,"max_cpc":68,"actual_cpc":68},59526,"data-science-manager-gbr006-refinitiv-limited","Data Science Manager",null,false,{"name":13,"slug":14,"logo_url":10},"Refinitiv Limited","refinitiv-limited",[16],"London",[18],"GB","hybrid",120000,180000,"EUR","estimated",[25],"FULL_TIME","permanent",{"ci\u002Fcd":28,"devops":28,"python":29,"pytorch":29,"langchain":29,"kubernetes":28,"tensorflow":29,"azure openai":29,"hugging face":29,"scikit-learn":29,"aws ai services":29,"azure ai search":29,"semantic kernel":29,"azure ai foundry":29,"azure machine learning":29},3,4,[31,32,33,34,35,36,37,38,39,40,41,42,43,44,45],"Python","PyTorch","TensorFlow","Scikit-Learn","Hugging Face","LangChain","Semantic Kernel","Azure AI Foundry","Azure Machine Learning","Azure OpenAI","Azure AI Search","AWS AI Services","Kubernetes","CI\u002FCD","DevOps",{"rag":29,"llms":29,"mlops":29,"llmops":29,"agentic ai":29,"statistics":29,"probability":29,"optimization":29,"transformers":29,"deep learning":29,"generative ai":29,"responsible ai":29,"capital markets":28,"experimentation":29,"machine learning":29,"model evaluation":29,"model governance":29,"financial services":28,"product management":28,"project management":28},[48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67],"Machine Learning","Deep Learning","LLMs","Generative AI","RAG","Agentic AI","Transformers","Statistics","Probability","Optimization","Experimentation","MLOps","LLMOps","Model Evaluation","Model Governance","Responsible AI","Financial Services","Capital Markets","Product Management","Project Management",1,{"id":70,"slug":71,"title":72,"raw_title":10,"is_featured":11,"company":73,"raw_hiringOrganization_logo_url":10,"processed_city_gmaps":74,"processed_country_iso_code_gmaps":75,"processed_home_office":76,"processed_salary_min":77,"processed_salary_max":20,"processed_salary_currency":78,"processed_salary_source":23,"processed_working_hours":79,"processed_employment_types":26,"processed_it_skills":80,"processed_it_skills_labels":81,"processed_job_expertise_skills":90,"processed_job_expertise_skills_labels":91,"max_cpc":68,"actual_cpc":68},59530,"data-scientist-gbr006-refinitiv-limited","Data Scientist",{"name":13,"slug":14,"logo_url":10},[16],[18],"onsite",80000,"GBP",[25],{"sql":28,"llms":28,"mlops":28,"numpy":28,"pandas":28,"python":29,"scikit-learn":28,"generative ai":28,"azure ai services":4,"rag architectures":28,"data visualization":28,"cloud-based data science platforms":28},[31,82,83,84,85,51,50,86,87,59,88,89],"SQL","Pandas","NumPy","Scikit-learn","RAG architectures","Cloud-based data science platforms","Data visualization","Azure AI services",{"sre":4,"mentoring":28,"observability":4,"responsible ai":4,"experimentation":28,"machine learning":29,"model evaluation":28,"model governance":28,"model monitoring":28,"product delivery":28,"financial services":4,"feature engineering":28,"predictive analytics":29,"ai-powered automation":4,"market infrastructure":4,"operational analytics":4,"statistical modelling":29,"regulated environments":4},[48,92,93,58,94,61,95,62,96,97,64,98,99,100,101,102,103,63],"Statistical Modelling","Predictive Analytics","Feature Engineering","Model Monitoring","Product Delivery","Mentoring","Regulated Environments","Market Infrastructure","Observability","SRE","Operational Analytics","AI-powered Automation",{"image_path":10,"content_de":10,"content_en":105,"composite_key":118,"last_updated":119},{"tab1":106,"tab2":109,"tab3":112,"tab4":115},{"title":107,"content":108},"Strategic Importance","In the dynamic financial landscape of the United Kingdom, experimentation has emerged as a cornerstone of innovation and competitive advantage. Financial institutions are increasingly adopting experimental approaches to refine products, optimize customer experiences, and drive operational efficiency. This expertise is not just about running A\u002FB tests; it encompasses a mindset of continuous learning and data-driven decision-making. Professionals skilled in experimentation are pivotal in transforming insights into actionable strategies, reducing risk, and accelerating growth. In the UK, where the financial sector is a global hub, the demand for such talent is soaring. Beyond core experimentation, related expertise such as [Responsible Ai](\u002Fen-gb\u002Fjobs-by-expertise\u002Fresponsible-ai), [Machine Learning](\u002Fen-gb\u002Fjobs-by-expertise\u002Fmachine-learning), [Model Evaluation](\u002Fen-gb\u002Fjobs-by-expertise\u002Fmodel-evaluation) further enhances an individual's ability to deliver impactful results. As organizations strive to stay ahead, the strategic importance of experimentation cannot be overstated—it is the engine of innovation and the key to unlocking sustainable success in a rapidly evolving market.",{"title":110,"content":111},"Top Industries & Locations","Experimentation roles in the United Kingdom are concentrated in dynamic sectors that thrive on data and innovation. The leading industries for these positions include [Financial Markets Infrastructure](\u002Fen-gb\u002Fjobs-by-industry\u002Ffinancial-markets-infrastructure), [Data](\u002Fen-gb\u002Fjobs-by-industry\u002Fdata), where companies are leveraging experimental methods to enhance customer engagement, streamline operations, and develop cutting-edge financial products. Geographically, the hotspots for experimentation jobs are [London](\u002Fen-gb\u002Fjobs-in-london), which are home to a vibrant ecosystem of financial institutions, tech startups, and corporate innovation hubs. These locations offer a rich pool of talent and a culture that embraces change and creativity. Whether in the bustling financial districts or emerging tech clusters, professionals in experimentation find abundant opportunities to make a significant impact. As the UK continues to solidify its position as a global financial leader, the demand for experimentation expertise across these industries and locations is expected to grow, making it an exciting and rewarding career path.",{"title":113,"content":114},"In-Demand Skills & Employers","To excel in experimentation roles in the United Kingdom, professionals must possess a blend of analytical, technical, and strategic skills. Key in-demand skills include [Python](\u002Fen-gb\u002Fjobs-by-skill\u002Fpython), [Scikit-learn](\u002Fen-gb\u002Fjobs-by-skill\u002Fscikit-learn), [Ci\u002Fcd](\u002Fen-gb\u002Fjobs-by-skill\u002Fcicd), which are essential for designing robust experiments, analyzing results, and deriving actionable insights. Additionally, a strong foundation in statistics, hypothesis testing, and user behavior analysis is crucial. Employers in the UK, including prominent names such as [Refinitiv Limited](\u002Fen-gb\u002Fcompany\u002Frefinitiv-limited), are actively seeking candidates who can drive innovation through experimentation. These organizations value individuals who can not only execute experiments but also communicate findings effectively to stakeholders and influence decision-making. With the right skill set, professionals can position themselves as invaluable assets in a competitive job market. As companies increasingly recognize the value of experimentation, the demand for these skills will continue to rise, offering excellent career prospects for those who invest in their development.",{"title":116,"content":117},"Career Path & Salary","A career in experimentation in the United Kingdom offers a rewarding trajectory with competitive compensation. Entry-level positions typically start at €120k, while experienced professionals can earn up to €180k. The median salary for experimentation roles is €180k, with the middle 50% of earners falling within the range of €180k – €180k. Currently, there are 2 open positions across the UK, reflecting a robust demand for this expertise. Career progression often follows a path from experimentation analyst to senior manager or director of experimentation, with opportunities to specialize in areas such as product experimentation, marketing optimization, or data science. As professionals gain experience and demonstrate impact, they can expect salary growth and increased responsibility. With the financial sector's ongoing digital transformation, the career outlook for experimentation specialists is exceptionally bright, offering both financial rewards and the chance to shape the future of finance.","expertise:experimentation:gb","2026-08-17T19:55:01.031520+02:00",{"industry":121,"employment_type":128,"expertise_skills":131,"it_skills":187,"salary_currency":248,"processed_working_hours":251},[122,125],{"key":123,"label":124,"count":4},"financial markets infrastructure","Financial Markets Infrastructure",{"key":126,"label":127,"count":4},"data","Data",[129],{"key":26,"label":130,"count":4},"PERMANENT",[132,134,137,139,141,143,145,148,151,153,155,158,160,162,164,166,168,170,172,174,177,180,182,185],{"key":133,"label":64,"slug":133,"count":4},"financial-services",{"key":135,"label":136,"slug":135,"count":4},"responsible-ai","Responsible Ai",{"key":138,"label":58,"slug":138,"count":4},"experimentation",{"key":140,"label":48,"slug":140,"count":4},"machine-learning",{"key":142,"label":61,"slug":142,"count":4},"model-evaluation",{"key":144,"label":62,"slug":144,"count":4},"model-governance",{"key":146,"label":147,"slug":146,"count":68},"llmops","Llmops",{"key":149,"label":150,"slug":149,"count":68},"llms","Llms",{"key":152,"label":99,"slug":152,"count":68},"market-infrastructure",{"key":154,"label":97,"slug":154,"count":68},"mentoring",{"key":156,"label":157,"slug":156,"count":68},"mlops","Mlops",{"key":159,"label":95,"slug":159,"count":68},"model-monitoring",{"key":161,"label":100,"slug":161,"count":68},"observability",{"key":163,"label":102,"slug":163,"count":68},"operational-analytics",{"key":165,"label":57,"slug":165,"count":68},"optimization",{"key":167,"label":93,"slug":167,"count":68},"predictive-analytics",{"key":169,"label":56,"slug":169,"count":68},"probability",{"key":171,"label":96,"slug":171,"count":68},"product-delivery",{"key":173,"label":66,"slug":173,"count":68},"product-management",{"key":175,"label":176,"slug":175,"count":68},"project-management","Project management",{"key":178,"label":179,"slug":178,"count":68},"rag","Rag",{"key":181,"label":98,"slug":181,"count":68},"regulated-environments",{"key":183,"label":184,"slug":183,"count":68},"sre","Sre",{"key":186,"label":92,"slug":186,"count":68},"statistical-modelling",[188,190,192,195,198,200,203,206,209,212,215,218,220,222,225,226,227,230,232,235,238,240,242,245],{"key":189,"label":34,"slug":189,"count":4},"scikit-learn",{"key":191,"label":31,"slug":191,"count":4},"python",{"key":193,"label":194,"slug":193,"count":68},"azure-ai-search","Azure Ai Search",{"key":196,"label":197,"slug":196,"count":68},"azure-ai-services","Azure Ai Services",{"key":199,"label":39,"slug":199,"count":68},"azure-machine-learning",{"key":201,"label":202,"slug":201,"count":68},"azure-openai","Azure Openai",{"key":204,"label":205,"slug":204,"count":68},"cicd","Ci\u002FCd",{"key":207,"label":208,"slug":207,"count":68},"cloud-based-data-science-platforms","Cloud-Based Data Science Platforms",{"key":210,"label":211,"slug":210,"count":68},"data-visualization","Data Visualization",{"key":213,"label":214,"slug":213,"count":68},"devops","Devops",{"key":216,"label":217,"slug":216,"count":68},"generative-ai","Generative Ai",{"key":219,"label":35,"slug":219,"count":68},"hugging-face",{"key":221,"label":43,"slug":221,"count":68},"kubernetes",{"key":223,"label":224,"slug":223,"count":68},"langchain","Langchain",{"key":149,"label":150,"slug":149,"count":68},{"key":156,"label":157,"slug":156,"count":68},{"key":228,"label":229,"slug":228,"count":68},"numpy","Numpy",{"key":231,"label":83,"slug":231,"count":68},"pandas",{"key":233,"label":234,"slug":233,"count":68},"pytorch","Pytorch",{"key":236,"label":237,"slug":236,"count":68},"rag-architectures","Rag Architectures",{"key":239,"label":37,"slug":239,"count":68},"semantic-kernel",{"key":241,"label":82,"slug":241,"count":68},"sql",{"key":243,"label":244,"slug":243,"count":68},"aws-ai-services","Aws Ai Services",{"key":246,"label":247,"slug":246,"count":68},"tensorflow","Tensorflow",[249,250],{"key":22,"label":22,"count":68},{"key":78,"label":78,"count":68},[252],{"key":25,"label":25,"count":4},{"total":254,"jobs":255},0,[]]