[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"seo-content-skill-xgboost-gb":3,"job-search-\u002Fde-gb\u002Fjobs-by-skill\u002Fxgboost":4,"skill-page-filters-\u002Fde-gb\u002Fjobs-by-skill\u002Fxgboost":133,"featured-jobs-\u002Fde-gb\u002Fjobs-by-skill\u002Fxgboost":255},{},{"total":5,"jobs":6},2,[7,54],{"id":8,"slug":9,"title":10,"raw_title":11,"is_featured":12,"company":13,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":16,"processed_country_iso_code_gmaps":18,"processed_home_office":20,"processed_salary_min":21,"processed_salary_max":22,"processed_salary_currency":23,"processed_salary_source":24,"processed_working_hours":25,"processed_employment_types":27,"processed_it_skills":28,"processed_it_skills_labels":30,"processed_job_expertise_skills":37,"processed_job_expertise_skills_labels":39,"max_cpc":53,"actual_cpc":53},71536,"quantitative-researcher-cmc-markets-uk-plc","Quantitative Researcher",null,false,{"name":14,"slug":15,"logo_url":11},"CMC Markets UK Plc","cmc-markets-uk-plc",[17],"London",[19],"GB","onsite",80000,120000,"GBP","estimated",[26],"FULL_TIME","permanent",{"sql":29,"python":29,"pytorch":29,"xgboost":29,"tensorflow":29,"scikit-learn":29},4,[31,32,33,34,35,36],"Python","SQL","scikit-learn","XGBoost","PyTorch","TensorFlow",{"bias detection":38,"risk management":29,"cross-validation":29,"machine learning":29,"model governance":38,"experiment design":29,"financial modeling":29,"model explainability":38,"time-series analysis":29,"out-of-sample testing":29,"production monitoring":38,"quantitative research":29,"overfitting prevention":38},3,[40,41,42,43,44,45,46,47,48,49,50,51,52],"Quantitative Research","Machine Learning","Time-Series Analysis","Financial Modeling","Risk Management","Model Governance","Model Explainability","Bias Detection","Overfitting Prevention","Production Monitoring","Experiment Design","Cross-Validation","Out-of-Sample Testing",1,{"id":55,"slug":56,"title":57,"raw_title":11,"is_featured":12,"company":58,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":61,"processed_country_iso_code_gmaps":62,"processed_home_office":20,"processed_salary_min":22,"processed_salary_max":63,"processed_salary_currency":23,"processed_salary_source":24,"processed_working_hours":64,"processed_employment_types":27,"processed_it_skills":65,"processed_it_skills_labels":66,"processed_job_expertise_skills":81,"processed_job_expertise_skills_labels":82,"max_cpc":53,"actual_cpc":53},59582,"principal-machine-learning-engineer-gbr006-refinitiv-limited","Principal Machine Learning Engineer",{"name":59,"slug":60,"logo_url":11},"Refinitiv Limited","refinitiv-limited",[17],[19],180000,[26],{"iam":29,"shap":29,"ci\u002Fcd":29,"mlops":29,"python":29,"pytorch":29,"xgboost":29,"telemetry":29,"tensorflow":29,"aws sagemaker":29,"observability":29,"data pipelines":29,"explainability":29,"feature stores":38,"drift detection":29,"gpu optimization":38,"model governance":29,"distributed training":38,"infrastructure as code":29},[31,67,35,36,34,68,69,70,71,45,72,73,74,75,76,77,78,79,80],"AWS SageMaker","SHAP","CI\u002FCD","Infrastructure as Code","MLOps","Explainability","Drift Detection","Observability","Telemetry","IAM","Data Pipelines","Feature Stores","Distributed Training","GPU Optimization",{"slos":29,"encryption":29,"versioning":29,"a\u002Fb testing":29,"ml security":29,"model cards":29,"auditability":29,"pii handling":29,"reason codes":29,"traceability":29,"scoring logic":29,"ranking models":38,"stem education":38,"canary rollouts":29,"entity matching":38,"golden datasets":29,"model hot paths":29,"reproducibility":29,"benchmark suites":29,"model validation":29,"privacy policies":29,"search relevance":38,"behavioural tests":29,"cost optimization":29,"cross-account iam":29,"data minimisation":29,"model calibration":29,"proactive failover":29,"scale optimization":29,"security standards":29,"shadow deployments":29,"compliance policies":29,"feature engineering":29,"shadow-mode testing":29,"telemetry pipelines":29,"similarity modelling":38,"confidence thresholds":29,"continuous validation":29,"regulatory compliance":29,"feature store adoption":38,"data quality guardrails":29,"optimization strategies":29,"performance engineering":29,"compliance documentation":29,"reliability optimization":29,"data minimisation policies":29,"model lifecycle management":29,"latency-sensitive inference":29,"machine learning architecture":29,"multi-account aws ml platforms":38},[83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132],"Machine Learning Architecture","Model Lifecycle Management","Model Validation","Performance Engineering","Security Standards","Compliance Documentation","Model Cards","A\u002FB Testing","Shadow Deployments","Canary Rollouts","Ranking Models","Search Relevance","Entity Matching","Similarity Modelling","Feature Engineering","Data Quality Guardrails","Model Calibration","Scoring Logic","Confidence Thresholds","Optimization Strategies","Reason Codes","Regulatory Compliance","Data Minimisation","PII Handling","Encryption","Auditability","Reproducibility","Versioning","Traceability","Golden Datasets","Behavioural Tests","Benchmark Suites","Latency-Sensitive Inference","Model Hot Paths","Cost Optimization","Scale Optimization","Reliability Optimization","SLOs","Telemetry Pipelines","Privacy Policies","Data Minimisation Policies","Compliance Policies","Proactive Failover","Shadow-Mode Testing","Continuous Validation","ML Security","Cross-Account IAM","Multi-Account AWS ML Platforms","Feature Store Adoption","STEM Education",{"industry":134,"employment_type":144,"expertise_skills":147,"it_skills":199,"salary_currency":251,"processed_working_hours":253},[135,138,141],{"key":136,"label":137,"count":53},"financial markets infrastructure","Financial Markets Infrastructure",{"key":139,"label":140,"count":53},"data","Data",{"key":142,"label":143,"count":53},"financial services","Financial Services",[145],{"key":27,"label":146,"count":5},"PERMANENT",[148,150,152,154,156,159,161,163,165,167,169,171,173,175,177,179,181,184,186,188,191,193,195,197],{"key":149,"label":88,"slug":149,"count":53},"compliance-documentation",{"key":151,"label":105,"slug":151,"count":53},"data-minimisation",{"key":153,"label":113,"slug":153,"count":53},"behavioural-tests",{"key":155,"label":96,"slug":155,"count":53},"similarity-modelling",{"key":157,"label":158,"slug":157,"count":53},"cross-account-iam","Cross-Account Iam",{"key":160,"label":131,"slug":160,"count":53},"feature-store-adoption",{"key":162,"label":103,"slug":162,"count":53},"reason-codes",{"key":164,"label":49,"slug":164,"count":53},"production-monitoring",{"key":166,"label":97,"slug":166,"count":53},"feature-engineering",{"key":168,"label":101,"slug":168,"count":53},"confidence-thresholds",{"key":170,"label":91,"slug":170,"count":53},"shadow-deployments",{"key":172,"label":83,"slug":172,"count":53},"machine-learning-architecture",{"key":174,"label":51,"slug":174,"count":53},"cross-validation",{"key":176,"label":108,"slug":176,"count":53},"auditability",{"key":178,"label":119,"slug":178,"count":53},"reliability-optimization",{"key":180,"label":100,"slug":180,"count":53},"scoring-logic",{"key":182,"label":183,"slug":182,"count":53},"stem-education","Stem Education",{"key":185,"label":112,"slug":185,"count":53},"golden-datasets",{"key":187,"label":45,"slug":187,"count":53},"model-governance",{"key":189,"label":190,"slug":189,"count":53},"pii-handling","Pii Handling",{"key":192,"label":126,"slug":192,"count":53},"shadow-mode-testing",{"key":194,"label":127,"slug":194,"count":53},"continuous-validation",{"key":196,"label":40,"slug":196,"count":53},"quantitative-research",{"key":198,"label":121,"slug":198,"count":53},"telemetry-pipelines",[200,203,205,208,211,214,216,219,221,223,225,227,229,232,234,237,239,242,245,248,250],{"key":201,"label":202,"slug":201,"count":5},"xgboost","Xgboost",{"key":204,"label":31,"slug":204,"count":5},"python",{"key":206,"label":207,"slug":206,"count":5},"pytorch","Pytorch",{"key":209,"label":210,"slug":209,"count":5},"tensorflow","Tensorflow",{"key":212,"label":213,"slug":212,"count":53},"mlops","Mlops",{"key":215,"label":74,"slug":215,"count":53},"observability",{"key":217,"label":218,"slug":217,"count":53},"aws-sagemaker","Aws Sagemaker",{"key":220,"label":72,"slug":220,"count":53},"explainability",{"key":33,"label":222,"slug":33,"count":53},"Scikit-Learn",{"key":224,"label":73,"slug":224,"count":53},"drift-detection",{"key":226,"label":75,"slug":226,"count":53},"telemetry",{"key":228,"label":32,"slug":228,"count":53},"sql",{"key":230,"label":231,"slug":230,"count":53},"gpu-optimization","Gpu Optimization",{"key":233,"label":78,"slug":233,"count":53},"feature-stores",{"key":235,"label":236,"slug":235,"count":53},"iam","Iam",{"key":238,"label":77,"slug":238,"count":53},"data-pipelines",{"key":240,"label":241,"slug":240,"count":53},"cicd","Ci\u002FCd",{"key":243,"label":244,"slug":243,"count":53},"shap","Shap",{"key":246,"label":247,"slug":246,"count":53},"infrastructure-as-code","Infrastructure As Code",{"key":249,"label":79,"slug":249,"count":53},"distributed-training",{"key":187,"label":45,"slug":187,"count":53},[252],{"key":23,"label":23,"count":5},[254],{"key":26,"label":26,"count":5},{"total":256,"jobs":257},0,[]]