[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"seo-content-expertise-machine-learning-es":3,"job-search-\u002Fde-es\u002Fjobs-by-expertise\u002Fmachine-learning":33,"expertise-filters-\u002Fde-es\u002Fjobs-by-expertise\u002Fmachine-learning":319,"featured-jobs-\u002Fde-es\u002Fjobs-by-expertise\u002Fmachine-learning":457},{"image_path":4,"content_de":5,"content_en":18,"composite_key":31,"last_updated":32},"\u002Fimages\u002Fexpertise\u002Fmachine-learning.webp",{"tab1":6,"tab2":9,"tab3":12,"tab4":15},{"title":7,"content":8},"Bedeutung & Relevanz","Maschinelles Lernen hat in Spanien eine enorme strategische Bedeutung erlangt, insbesondere im Finanzsektor. Die spanische Wirtschaft profitiert zunehmend von KI-gestützten Lösungen zur Prozessoptimierung, Risikobewertung und Kundenbetreuung. In Städten wie [Barcelona](\u002Fsearch) und [València](\u002Fsearch) setzen führende Unternehmen auf ML-Algorithmen für präzisere Prognosen und automatisierte Entscheidungsfindung. Die Nachfrage nach Experten in [Finanzanalyse](\u002Fjobs-by-expertise\u002Ffinancial-analysis) und [Risikomanagement](\u002Fjobs-by-expertise\u002Frisk-management) steigt kontinuierlich, da ML-Modelle helfen, Markttrends frühzeitig zu erkennen und Compliance-Anforderungen effizient umzusetzen. Mit der zunehmenden Digitalisierung wird maschinelles Lernen zum Schlüsselfaktor für Wettbewerbsfähigkeit und Innovation in Spaniens Finanzdienstleistungsbranche.",{"title":10,"content":11},"Top-Branchen & Standorte","In Spanien konzentriert sich die Nachfrage nach Maschinelles-Lernen-Experten vor allem auf die [Versicherungsbranche](\u002Fjobs-by-industry\u002Finsurance) und [Finanzdienstleistungen](\u002Fjobs-by-industry\u002Ffinancial-services). Metropolen wie [Barcelona](\u002Fsearch) und [València](\u002Fsearch) sind Hotspots für KI-Talente, wo Unternehmen innovative ML-Lösungen für Betrugserkennung, Kundenprofilierung und Portfoliomanagement entwickeln. Die [Versicherungsbranche](\u002Fjobs-by-industry\u002Finsurance) nutzt prädiktive Modelle zur Schadensvorhersage und Tarifgestaltung, während [Finanzdienstleistungen](\u002Fjobs-by-industry\u002Ffinancial-services) ML für algorithmischen Handel und Kreditwürdigkeitsprüfungen einsetzen. Diese Standorte bieten exzellente Karrierechancen in dynamischen FinTech-Ökosystemen.",{"title":13,"content":14},"Gefragte Skills & Arbeitgeber","Führende Unternehmen wie Allianz Insurance und CO_SANAGSL Apex Financial Services Spain, SL suchen in Spanien nach ML-Experten mit Spezialisierungen in [Datenmanagement](\u002Fjobs-by-expertise\u002Fdata-management), [Datenanalyse](\u002Fjobs-by-expertise\u002Fdata-analysis) und [Projektmanagement](\u002Fjobs-by-expertise\u002Fproject-management). Gefragte Kompetenzen umfassen [Datenanalyse](\u002Fjobs-by-expertise\u002Fdata-analysis), [Datenplattform-Design](\u002Fjobs-by-expertise\u002Fdata-platform-design), [Cloud-Architektur](\u002Fjobs-by-expertise\u002Fcloud-architecture) und [Enterprise-Architektur](\u002Fjobs-by-expertise\u002Fenterprise-architecture). Diese Arbeitgeber integrieren ML in ihre Kernprozesse, von der automatisierten Schadensregulierung bei Allianz bis zur KI-gestützten Portfolioptimierung bei CO_SANAGSL. Kenntnisse in [Datenanalyse](\u002Fjobs-by-expertise\u002Fdata-analysis) und [Projektmanagement](\u002Fjobs-by-expertise\u002Fproject-management) sind besonders wertvoll für die Umsetzung skalierbarer ML-Lösungen.",{"title":16,"content":17},"Karriere & Entwicklung","Karrierewege im Maschinelles Lernen in Spanien reichen vom Data Scientist bis zum ML-Architekten. Erfolgreiche Professionals kombinieren [SQL](\u002Fjobs-by-skill\u002Fsql), [Python](\u002Fjobs-by-skill\u002Fpython) und Cloud-Kenntnisse mit Domänenexpertise in [Finanzanalyse](\u002Fjobs-by-expertise\u002Ffinancial-analysis) und [Risikomanagement](\u002Fjobs-by-expertise\u002Frisk-management). Fortbildungen in [Datenanalyse](\u002Fjobs-by-expertise\u002Fdata-analysis), [Projektmanagement](\u002Fjobs-by-expertise\u002Fproject-management) und [Cloud-Computing](\u002Fjobs-by-expertise\u002Fcloud-computing) öffnen Türen zu Führungspositionen. Praktische Erfahrung mit [Python](\u002Fjobs-by-skill\u002Fpython), [SQL](\u002Fjobs-by-skill\u002Fsql) und [DevOps](\u002Fjobs-by-skill\u002Fdevops) ist entscheidend, ebenso wie Verständnis für [Datenanalyse](\u002Fjobs-by-expertise\u002Fdata-analysis) und [Projektmanagement](\u002Fjobs-by-expertise\u002Fproject-management) in agilen Umgebungen. Spanische Universitäten und Tech-Bootcamps bieten exzellente Ausbildungsmöglichkeiten für diese zukunftssichere Karriere.",{"tab1":19,"tab2":22,"tab3":25,"tab4":28},{"title":20,"content":21},"Strategic Importance","Machine Learning has become strategically vital for Spain's financial sector, driving innovation and competitive advantage across insurance and financial services. In Spain, ML enables companies to develop sophisticated risk assessment models, automate complex processes, and deliver personalized customer experiences at scale. The technology's ability to analyze vast datasets helps Spanish financial institutions optimize investment strategies, detect fraudulent activities in real-time, and enhance underwriting accuracy.\n\nSpanish companies are increasingly leveraging ML to navigate complex regulatory requirements while maintaining operational efficiency. The integration of ML with traditional financial services has created new revenue streams and improved decision-making capabilities across the sector. As Spain continues to digitalize its financial landscape, Machine Learning serves as a cornerstone technology for driving growth and maintaining market relevance in an increasingly competitive European financial ecosystem.",{"title":23,"content":24},"Top Industries & Locations","In Spain, Machine Learning expertise is particularly sought after within the [insurance](\u002Fjobs-by-industry\u002Finsurance) and [financial services](\u002Fjobs-by-industry\u002Ffinancial-services) sectors, where companies are rapidly adopting AI-driven solutions to enhance operational efficiency and customer engagement. The [insurance](\u002Fjobs-by-industry\u002Finsurance) industry leverages ML for advanced risk modeling, claims processing automation, and personalized policy recommendations, while [financial services](\u002Fjobs-by-industry\u002Ffinancial-services) firms utilize these technologies for fraud detection, investment optimization, and customer behavior analysis.\n\nGeographically, [Barcelona](\u002Fjobs-in-barcelona) and [València](\u002Fjobs-in-valencia) emerge as primary hubs for ML talent in Spain's financial sector. [Barcelona](\u002Fjobs-in-barcelona) hosts numerous fintech startups and established financial institutions implementing ML solutions, benefiting from its strong technology ecosystem and academic partnerships. [València](\u002Fjobs-in-valencia) has developed a growing reputation for financial technology innovation, with companies increasingly seeking ML professionals to drive digital transformation initiatives across the region's financial services landscape.",{"title":26,"content":27},"In-Demand Skills & Employers","Leading Spanish financial institutions actively seek Machine Learning professionals with complementary expertise in [data privacy](\u002Fjobs-by-expertise\u002Fdata-privacy), [data security](\u002Fjobs-by-expertise\u002Fdata-security), [cloud migration](\u002Fjobs-by-expertise\u002Fcloud-migration), and [data management](\u002Fjobs-by-expertise\u002Fdata-management). The integration of [large language models](\u002Fjobs-by-expertise\u002Flarge-language-models) and [agentic AI](\u002Fjobs-by-expertise\u002Fagentic-ai) has become particularly valuable for enhancing customer service and operational automation in Spain's financial sector.\n\nMajor employers driving ML adoption include [Allianz Insurance](\u002Fcompany\u002Fallianz-insurance) and [CO_SANAGSL Apex Financial Services Spain, SL](\u002Fcompany\u002Fco_sanagsl-apex-financial-services-spain-sl), both leveraging advanced ML capabilities for risk assessment, customer segmentation, and process optimization. These companies require professionals skilled in [system integration](\u002Fjobs-by-expertise\u002Fsystem-integration), [data platform design](\u002Fjobs-by-expertise\u002Fdata-platform-design), and [cloud architecture](\u002Fjobs-by-expertise\u002Fcloud-architecture) to successfully implement ML solutions that meet Spain's specific regulatory and market requirements while maintaining competitive advantage in the evolving financial landscape.",{"title":29,"content":30},"Career & Development","Machine Learning careers in Spain's financial sector typically progress from data analyst roles to ML engineer positions, with opportunities advancing to lead data scientist and AI strategy director levels. Professionals can enhance their career trajectory by developing expertise in complementary areas such as [data science](\u002Fjobs-by-expertise\u002Fdata-science), [natural language processing](\u002Fjobs-by-expertise\u002Fnatural-language-processing), and [project management](\u002Fjobs-by-expertise\u002Fproject-management), which are increasingly integrated with ML implementations in Spanish financial institutions.\n\nTechnical skill development should focus on mastering [Python](\u002Fjobs-by-skill\u002Fpython) and [SQL](\u002Fjobs-by-skill\u002Fsql) as foundational programming languages, complemented by cloud platforms like [Amazon Web Services](\u002Fjobs-by-skill\u002Famazon-web-services) and [Microsoft Azure](\u002Fjobs-by-skill\u002Fmicrosoft-azure). Specialized ML frameworks including [PyTorch](\u002Fjobs-by-skill\u002Fpytorch) and [TensorFlow](\u002Fjobs-by-skill\u002Ftensorflow) are essential for building sophisticated models, while [DevOps](\u002Fjobs-by-skill\u002Fdevops) practices and [CI\u002FCD](\u002Fjobs-by-skill\u002Fci-cd) pipelines ensure efficient deployment and maintenance of ML systems in Spain's dynamic financial environment. Continuous learning in [cloud computing](\u002Fjobs-by-skill\u002Fcloud-computing) and [data governance](\u002Fjobs-by-expertise\u002Fdata-governance) further enhances career advancement opportunities.","expertise:machine-learning:es","2026-08-17T09:09:33.846631+02:00",{"total":34,"jobs":35},8,[36,86,119,144,181,217,256,286],{"id":37,"slug":38,"title":39,"raw_title":40,"is_featured":41,"company":42,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":46,"processed_country_iso_code_gmaps":48,"processed_home_office":50,"processed_salary_min":51,"processed_salary_max":52,"processed_salary_currency":53,"processed_salary_source":54,"processed_working_hours":55,"processed_employment_types":57,"processed_it_skills":58,"processed_it_skills_labels":61,"processed_job_expertise_skills":73,"processed_job_expertise_skills_labels":74,"max_cpc":85,"actual_cpc":85},81806,"data-ai-solutions-expert-mfd3400-allianz-insurance","Data & AI Solutions Expert (m\u002Ff\u002Fd)_3400",null,false,{"name":43,"slug":44,"logo_url":45},"Allianz Insurance","allianz-insurance","https:\u002F\u002Fcdn.phenompeople.com\u002FCareerConnectResources\u002FAISAIPGB\u002Fimages\u002FHeader-1706868786965.svg",[47],"BARCELONA",[49],"ES","hybrid",80000,120000,"EUR","estimated",[56],"FULL_TIME","permanent",{"etl":59,"python":59,"power bi":59,"ml libraries":59,"data analytics":59,"data pipelines":59,"ai technologies":59,"genai platforms":60,"data warehousing":59,"data visualization":59,"microsoft cloud platform":59},4,3,[62,63,64,65,66,67,68,69,70,71,72],"Python","ML libraries","Power BI","Microsoft cloud platform","ETL","Data Warehousing","Data Pipelines","Data Analytics","Data Visualization","AI technologies","GenAI platforms",{"data quality":59,"data strategy":59,"data governance":59,"data management":59,"machine learning":59,"business planning":59,"advanced analytics":59,"transformation programs":59,"data & ai solution delivery":59,"data & ai project management":59},[75,76,77,78,79,80,81,82,83,84],"Data & AI Solution Delivery","Data & AI Project Management","Data Strategy","Data Management","Data Quality","Data Governance","Advanced Analytics","Machine Learning","Business Planning","Transformation Programs",1,{"id":87,"slug":88,"title":89,"raw_title":40,"is_featured":41,"company":90,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":91,"processed_country_iso_code_gmaps":92,"processed_home_office":50,"processed_salary_min":93,"processed_salary_max":94,"processed_salary_currency":53,"processed_salary_source":54,"processed_working_hours":95,"processed_employment_types":57,"processed_it_skills":96,"processed_it_skills_labels":97,"processed_job_expertise_skills":111,"processed_job_expertise_skills_labels":112,"max_cpc":85,"actual_cpc":85},81665,"senior-analytics-ai-engineer-allianz-insurance","Senior Analytics & AI Engineer",{"name":43,"slug":44,"logo_url":45},[47],[49],60000,90000,[56],{"dax":59,"sql":59,"llms":60,"python":59,"celonis":60,"pyspark":60,"azure ai":60,"power bi":59,"ai agents":60,"power query":59,"azure openai":60,"copilot studio":60,"azure ai foundry":60,"azure data platform":60,"retrieval-augmented generation (rag)":60},[98,62,64,99,100,101,102,103,104,105,106,107,108,109,110],"SQL","PySpark","Azure Data Platform","Azure AI","Azure OpenAI","Azure AI Foundry","Copilot Studio","LLMs","Retrieval-Augmented Generation (RAG)","AI Agents","DAX","Power Query","Celonis",{"data modeling":59,"process mining":60,"data governance":59,"machine learning":60,"ai solution design":59,"data product design":59,"business translation":59,"semantic model design":59},[113,114,115,116,82,80,117,118],"Data Modeling","Data Product Design","Semantic Model Design","AI Solution Design","Process Mining","Business Translation",{"id":120,"slug":121,"title":122,"raw_title":40,"is_featured":41,"company":123,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":124,"processed_country_iso_code_gmaps":126,"processed_home_office":50,"processed_salary_min":127,"processed_salary_max":128,"processed_salary_currency":53,"processed_salary_source":54,"processed_working_hours":129,"processed_employment_types":57,"processed_it_skills":130,"processed_it_skills_labels":131,"processed_job_expertise_skills":135,"processed_job_expertise_skills_labels":136,"max_cpc":85,"actual_cpc":85},71342,"ml-engineer-allianz-insurance","ML Engineer",{"name":43,"slug":44,"logo_url":45},[125],"MADRID",[49],45000,65000,[56],{"sql":59,"mlops":60,"spark":60,"python":59,"microsoft azure":60},[62,98,132,133,134],"Spark","Microsoft Azure","MLOps",{"big data":60,"churn modeling":59,"data pipelines":59,"machine learning":59,"model deployment":60,"retention metrics":60,"insurance knowledge":60,"predictive modeling":59,"portfolio management":60},[82,137,138,68,139,140,141,142,143],"Predictive Modeling","Churn Modeling","Big Data","Model Deployment","Insurance Knowledge","Retention Metrics","Portfolio Management",{"id":145,"slug":146,"title":147,"raw_title":40,"is_featured":41,"company":148,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":151,"processed_country_iso_code_gmaps":153,"processed_home_office":154,"processed_salary_min":51,"processed_salary_max":52,"processed_salary_currency":53,"processed_salary_source":54,"processed_working_hours":155,"processed_employment_types":57,"processed_it_skills":156,"processed_it_skills_labels":157,"processed_job_expertise_skills":168,"processed_job_expertise_skills_labels":169,"max_cpc":85,"actual_cpc":85},69482,"global-market-risk-unit-quantitative-manager-cib-bcobilbao-vizcaya-argentaria","GLOBAL MARKET RISK UNIT QUANTITATIVE MANAGER - CIB",{"name":149,"slug":150,"logo_url":40},"BCO.BILBAO VIZCAYA ARGENTARIA","bcobilbao-vizcaya-argentaria",[152],"Bilbao",[49],"onsite",[56],{"c#":59,"c++":59,"git":60,"ci\u002Fcd":60,"numpy":59,"scipy":59,"docker":60,"pandas":59,"python":59,"pytorch":59,"tensorflow":59},[62,158,159,160,161,162,163,164,165,166,167],"C++","C#","NumPy","SciPy","Pandas","PyTorch","TensorFlow","Git","CI\u002FCD","Docker",{"xva":59,"mentoring":59,"data science":59,"machine learning":59,"derivative pricing":59,"project management":59,"market risk modeling":59,"financial engineering":59,"software architecture":59,"counterparty credit risk":59,"quantitative risk analysis":59,"regulatory frameworks (frtb, imm)":59},[170,171,172,173,174,175,176,177,82,178,179,180],"Quantitative Risk Analysis","Financial Engineering","Data Science","Market Risk Modeling","Counterparty Credit Risk","XVA","Derivative Pricing","Regulatory Frameworks (FRTB, IMM)","Software Architecture","Project Management","Mentoring",{"id":182,"slug":183,"title":184,"raw_title":40,"is_featured":41,"company":185,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":186,"processed_country_iso_code_gmaps":188,"processed_home_office":50,"processed_salary_min":93,"processed_salary_max":94,"processed_salary_currency":53,"processed_salary_source":54,"processed_working_hours":189,"processed_employment_types":57,"processed_it_skills":190,"processed_it_skills_labels":192,"processed_job_expertise_skills":201,"processed_job_expertise_skills_labels":202,"max_cpc":85,"actual_cpc":85},69476,"data-scientist-genai-llms-bcobilbao-vizcaya-argentaria","Data Scientist GenAI (LLMs)",{"name":149,"slug":150,"logo_url":40},[187],"Madrid",[49],[56],{"aws":191,"azure":191,"numpy":59,"docker":191,"pandas":59,"python":59,"pyspark":60,"pytorch":60,"langchain":191,"langgraph":191,"kubernetes":191,"tensorflow":60,"google cloud":191,"scikit-learn":59,"huggingface transformers":60},2,[62,162,160,193,99,164,163,194,195,196,197,198,199,167,200],"scikit-learn","HuggingFace Transformers","LangChain","LangGraph","AWS","Google Cloud","Azure","Kubernetes",{"ethical ai":60,"a\u002Fb testing":60,"data analysis":59,"cloud computing":191,"causal inference":191,"fine-tuning llms":59,"machine learning":59,"ai risk assessment":59,"model optimization":59,"prompt engineering":59,"statistical modeling":59,"embedding elicitation":59,"data lifecycle management":59,"large language models (llms)":59,"data privacy laws (gdpr, ccpa)":60},[203,82,204,205,206,207,208,209,210,211,212,213,214,215,216],"Statistical Modeling","Large Language Models (LLMs)","Fine-tuning LLMs","Prompt Engineering","Embedding Elicitation","Model Optimization","Data Analysis","Data Lifecycle Management","AI Risk Assessment","A\u002FB Testing","Ethical AI","Data Privacy Laws (GDPR, CCPA)","Causal Inference","Cloud Computing",{"id":218,"slug":219,"title":220,"raw_title":40,"is_featured":41,"company":221,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":222,"processed_country_iso_code_gmaps":223,"processed_home_office":50,"processed_salary_min":224,"processed_salary_max":52,"processed_salary_currency":53,"processed_salary_source":54,"processed_working_hours":225,"processed_employment_types":57,"processed_it_skills":226,"processed_it_skills_labels":227,"processed_job_expertise_skills":243,"processed_job_expertise_skills_labels":244,"max_cpc":85,"actual_cpc":85},69486,"senior-data-scientist-foundation-model-ai-factory-bcobilbao-vizcaya-argentaria","Senior Data Scientist - Foundation Model - AI Factory",{"name":149,"slug":150,"logo_url":40},[152],[49],70000,[56],{"lora":60,"python":59,"pytorch":59,"checkpointing":60,"experiment tracking":60,"memory optimization":60,"sequential modeling":59,"distributed training":59,"performance profiling":60,"optimization algorithms":59,"representation learning":59,"mixed precision training":60,"transformer architectures":59,"graph neural networks (gnn)":60,"software engineering practices":59,"parameter-efficient fine-tuning":60,"large language model (llm) pre-training":59},[62,163,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242],"Distributed Training","Transformer Architectures","Parameter-Efficient Fine-Tuning","LoRA","Experiment Tracking","Mixed Precision Training","Checkpointing","Memory Optimization","Performance Profiling","Graph Neural Networks (GNN)","Large Language Model (LLM) Pre-training","Sequential Modeling","Representation Learning","Optimization Algorithms","Software Engineering Practices",{"deep learning":59,"responsible ai":59,"risk management":60,"data preparation":59,"machine learning":59,"model evaluation":59,"scalable ai systems":59,"production deployment":59,"regulatory compliance":60,"financial data analysis":60,"research and development":59,"model architecture design":59},[82,245,246,247,248,249,250,251,252,253,254,255],"Deep Learning","Model Architecture Design","Data Preparation","Model Evaluation","Production Deployment","Financial Data Analysis","Risk Management","Regulatory Compliance","Research and Development","Scalable AI Systems","Responsible AI",{"id":257,"slug":258,"title":259,"raw_title":40,"is_featured":41,"company":260,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":261,"processed_country_iso_code_gmaps":263,"processed_home_office":50,"processed_salary_min":94,"processed_salary_max":264,"processed_salary_currency":53,"processed_salary_source":54,"processed_working_hours":265,"processed_employment_types":57,"processed_it_skills":266,"processed_it_skills_labels":267,"processed_job_expertise_skills":274,"processed_job_expertise_skills_labels":275,"max_cpc":85,"actual_cpc":85},46163,"senior-ai-engineer-allianz-insurance-3","Senior AI Engineer",{"name":43,"slug":44,"logo_url":45},[262],"Barcelona",[49],130000,[56],{"sql":59,"ci\u002Fcd":59,"spark":59,"mlflow":59,"python":59,"langchain":59,"databricks":59,"delta lake":59,"llamaindex":59,"azure openai":59,"azure data lake":59,"azure ai services":59},[62,98,132,268,102,269,270,271,272,195,273,166],"Azure AI services","Azure Data Lake","Databricks","MLflow","Delta Lake","LlamaIndex",{"nlp":59,"llms":59,"mlops":59,"agentic ai":59,"generative ai":59,"data engineering":59,"machine learning":59,"vector databases":59,"rag architectures":59,"cloud architecture":59,"project management":60,"model lifecycle management":59,"fine-tuning techniques (lora, rlhf, instruction tuning)":59},[82,276,277,105,278,279,280,134,281,282,283,284,285],"Generative AI","NLP","Agentic AI","RAG architectures","Vector databases","Model lifecycle management","Fine-tuning techniques (LoRA, RLHF, instruction tuning)","Cloud architecture","Data engineering","Project management",{"id":287,"slug":288,"title":289,"raw_title":40,"is_featured":41,"company":290,"raw_hiringOrganization_logo_url":40,"processed_city_gmaps":293,"processed_country_iso_code_gmaps":294,"processed_home_office":50,"processed_salary_min":295,"processed_salary_max":224,"processed_salary_currency":53,"processed_salary_source":54,"processed_working_hours":296,"processed_employment_types":57,"processed_it_skills":297,"processed_it_skills_labels":298,"processed_job_expertise_skills":302,"processed_job_expertise_skills_labels":303,"max_cpc":85,"actual_cpc":318},82969,"operations-specialist-regulatory-reporting-avp-930g-dws-international-gmbh-madrid-branch","Operations Specialist- Regulatory Reporting- AVP",{"name":291,"slug":292,"logo_url":40},"930G DWS International GmbH, Madrid Branch","930g-dws-international-gmbh-madrid-branch",[187],[49],50000,[56],{"vba":60,"excel":59,"python":60,"microsoft office":59},[299,300,301,62],"Microsoft Office","Excel","VBA",{"vag":60,"mmfr":60,"aifmd":60,"mifid":59,"crr ii":60,"priips":60,"ai tools":60,"solvency ii":60,"ecb reporting":60,"data analytics":60,"machine learning":191,"financial writing":60,"audit coordination":60,"project management":60,"workflow automation":60,"regulatory reporting":59,"process documentation":60},[304,305,306,307,308,309,310,311,312,313,314,315,179,316,82,317,69],"Regulatory Reporting","MiFID","PRIIPs","AIFMD","ECB Reporting","MMFR","CRR II","Solvency II","VAG","Financial Writing","Audit Coordination","Process Documentation","AI Tools","Workflow Automation",0.7,{"industry":320,"employment_type":333,"expertise_skills":336,"it_skills":394,"salary_currency":453,"processed_working_hours":455},[321,324,327,330],{"key":322,"label":323,"count":59},"insurance","Insurance",{"key":325,"label":326,"count":60},"financial services","Financial Services",{"key":328,"label":329,"count":85},"asset management","Asset Management",{"key":331,"label":332,"count":85},"banking","Banking",[334],{"key":57,"label":335,"count":34},"PERMANENT",[337,339,341,343,346,349,352,355,357,359,361,363,365,367,370,372,374,377,380,383,385,387,390,392],{"key":338,"label":82,"slug":338,"count":34},"machine-learning",{"key":340,"label":285,"slug":340,"count":60},"project-management",{"key":342,"label":80,"slug":342,"count":191},"data-governance",{"key":344,"label":345,"slug":344,"count":85},"ai-risk-assessment","Ai Risk Assessment",{"key":347,"label":348,"slug":347,"count":85},"ai-solution-design","Ai Solution Design",{"key":350,"label":351,"slug":350,"count":85},"ai-tools","Ai Tools",{"key":353,"label":354,"slug":353,"count":85},"aifmd","Aifmd",{"key":356,"label":314,"slug":356,"count":85},"audit-coordination",{"key":358,"label":139,"slug":358,"count":85},"big-data",{"key":360,"label":83,"slug":360,"count":85},"business-planning",{"key":362,"label":118,"slug":362,"count":85},"business-translation",{"key":364,"label":215,"slug":364,"count":85},"causal-inference",{"key":366,"label":138,"slug":366,"count":85},"churn-modeling",{"key":368,"label":369,"slug":368,"count":85},"cloud-architecture","Cloud Architecture",{"key":371,"label":216,"slug":371,"count":85},"cloud-computing",{"key":373,"label":174,"slug":373,"count":85},"counterparty-credit-risk",{"key":375,"label":376,"slug":375,"count":85},"crr-ii","Crr Ii",{"key":378,"label":379,"slug":378,"count":85},"data-ai-project-management","Data & Ai Project Management",{"key":381,"label":382,"slug":381,"count":85},"data-ai-solution-delivery","Data & Ai Solution Delivery",{"key":384,"label":209,"slug":384,"count":85},"data-analysis",{"key":386,"label":69,"slug":386,"count":85},"data-analytics",{"key":388,"label":389,"slug":388,"count":85},"data-engineering","Data Engineering",{"key":391,"label":210,"slug":391,"count":85},"data-lifecycle-management",{"key":393,"label":78,"slug":393,"count":85},"data-management",[395,397,400,402,404,406,409,412,414,417,420,423,426,429,431,432,434,436,438,440,443,445,447,450],{"key":396,"label":62,"slug":396,"count":34},"python",{"key":398,"label":399,"slug":398,"count":60},"pytorch","Pytorch",{"key":401,"label":98,"slug":401,"count":60},"sql",{"key":403,"label":162,"slug":403,"count":191},"pandas",{"key":405,"label":167,"slug":405,"count":191},"docker",{"key":407,"label":408,"slug":407,"count":191},"langchain","Langchain",{"key":410,"label":411,"slug":410,"count":191},"ms-powerbi","MS PowerBI",{"key":413,"label":132,"slug":413,"count":191},"spark",{"key":415,"label":416,"slug":415,"count":191},"tensorflow","Tensorflow",{"key":418,"label":419,"slug":418,"count":191},"cicd","Ci\u002FCd",{"key":421,"label":422,"slug":421,"count":191},"pyspark","Pyspark",{"key":424,"label":425,"slug":424,"count":191},"numpy","Numpy",{"key":427,"label":428,"slug":427,"count":191},"azure-openai","Azure Openai",{"key":430,"label":104,"slug":430,"count":85},"copilot-studio",{"key":386,"label":69,"slug":386,"count":85},{"key":433,"label":68,"slug":433,"count":85},"data-pipelines",{"key":435,"label":70,"slug":435,"count":85},"data-visualization",{"key":437,"label":67,"slug":437,"count":85},"data-warehousing",{"key":439,"label":270,"slug":439,"count":85},"databricks",{"key":441,"label":442,"slug":441,"count":85},"dax","Dax",{"key":444,"label":272,"slug":444,"count":85},"delta-lake",{"key":446,"label":228,"slug":446,"count":85},"distributed-training",{"key":448,"label":449,"slug":448,"count":85},"etl","Etl",{"key":451,"label":452,"slug":451,"count":85},"ms-excel","MS Excel",[454],{"key":53,"label":53,"count":34},[456],{"key":56,"label":56,"count":34},{"total":458,"jobs":459},0,[]]