[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"seo-content-skill-pytorch-global":3,"job-search-\u002Fde\u002Fjobs-by-skill\u002Fpytorch?page=2":4,"skill-page-filters-\u002Fde\u002Fjobs-by-skill\u002Fpytorch?page=2":698,"featured-jobs-\u002Fde\u002Fjobs-by-skill\u002Fpytorch?page=2":915},{},{"total":5,"jobs":6},87,[7,75,114,149,195,230,263,292,324,349,380,399,432,462,485,545,569,620,637,669],{"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":31,"processed_job_expertise_skills":52,"processed_job_expertise_skills_labels":53,"max_cpc":74,"actual_cpc":74},75138,"data-scientist-manager-refinitiv-india-shared-services-private-limited","Data Scientist Manager",null,false,{"name":14,"slug":15,"logo_url":11},"Refinitiv India Shared Services Private Limited","refinitiv-india-shared-services-private-limited",[17],"Bengaluru",[19],"IN","onsite",3000000,5000000,"INR","estimated",[26],"FULL_TIME","permanent",{"cpq":29,"sap":29,"sql":30,"oracle":29,"python":30,"siebel":29,"uipath":29,"celonis":29,"pyspark":30,"pytorch":30,"tableau":29,"xgboost":30,"aws glue":29,"power bi":29,"blue prism":29,"salesforce":29,"tensorflow":30,"scikit-learn":30,"power automate":29,"automation anywhere":29},3,4,[32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51],"Python","SQL","PySpark","Power BI","Tableau","Scikit-learn","XGBoost","TensorFlow","PyTorch","AWS Glue","Celonis","UiPath","Power Automate","Automation Anywhere","Blue Prism","Siebel","CPQ","SAP","Oracle","Salesforce",{"rpa":30,"automation":30,"erp systems":29,"dashboarding":30,"data science":30,"process mining":30,"kpi development":30,"anomaly detection":30,"people management":30,"advanced analytics":30,"customer operations":30,"order-to-cash (o2c)":30,"predictive modeling":30,"workflow automation":30,"process optimization":30,"business rules engine":30,"operational analytics":30,"prescriptive modeling":30,"digital transformation":30,"sales order management":30},[54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73],"Data Science","Advanced Analytics","Process Optimization","Automation","Order-to-Cash (O2C)","Sales Order Management","Customer Operations","Business Rules Engine","Process Mining","Workflow Automation","RPA","Predictive Modeling","Prescriptive Modeling","Anomaly Detection","Operational Analytics","KPI Development","Dashboarding","Digital Transformation","People Management","ERP Systems",1,{"id":76,"slug":77,"title":78,"raw_title":11,"is_featured":12,"company":79,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":82,"processed_country_iso_code_gmaps":84,"processed_home_office":20,"processed_salary_min":86,"processed_salary_max":87,"processed_salary_currency":88,"processed_salary_source":24,"processed_working_hours":89,"processed_employment_types":27,"processed_it_skills":90,"processed_it_skills_labels":91,"processed_job_expertise_skills":102,"processed_job_expertise_skills_labels":103,"max_cpc":74,"actual_cpc":74},70489,"machine-learning-engineer-bank-of-montreal","Machine Learning Engineer",{"name":80,"slug":81,"logo_url":11},"Bank of Montreal","bank-of-montreal",[83],"Toronto",[85],"CA",80000,175000,"USD",[26],{"aws":29,"git":29,"sql":29,"azure":29,"keras":30,"docker":29,"hadoop":29,"python":30,"jenkins":29,"pytorch":30,"kubernetes":29,"tensorflow":30,"apache spark":29,"scikit-learn":30,"google cloud platform":29},[32,33,39,40,37,92,93,94,95,96,97,98,99,100,101],"Keras","Apache Spark","Hadoop","Docker","Kubernetes","Jenkins","Git","AWS","Azure","Google Cloud Platform",{"statistics":29,"mathematics":29,"programming":30,"deep learning":30,"ml algorithms":30,"scaling models":30,"machine learning":30,"operations research":29,"computational thinking":30,"continuous integration and continuous delivery\u002Fdeployment":30},[104,105,106,107,108,109,110,111,112,113],"Mathematics","Statistics","Operations Research","Deep Learning","Machine Learning","Scaling Models","Continuous Integration and Continuous Delivery\u002FDeployment","ML Algorithms","Computational Thinking","Programming",{"id":115,"slug":116,"title":117,"raw_title":11,"is_featured":12,"company":118,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":121,"processed_country_iso_code_gmaps":123,"processed_home_office":125,"processed_salary_min":126,"processed_salary_max":127,"processed_salary_currency":128,"processed_salary_source":24,"processed_working_hours":129,"processed_employment_types":27,"processed_it_skills":130,"processed_it_skills_labels":131,"processed_job_expertise_skills":141,"processed_job_expertise_skills_labels":142,"max_cpc":74,"actual_cpc":74},69576,"data-scientist-associate-ai-performance-evolution-ciudad-de-mexico-bbva-mexico-sa","Data Scientist Associate – AI Performance & Evolution (Ciudad de México)",{"name":119,"slug":120,"logo_url":11},"BBVA MÉXICO S.A.","bbva-mexico-sa",[122],"Mexiko-Stadt",[124],"MX","hybrid",600000,900000,"MXN",[26],{"rag":29,"llms":29,"ci\u002Fcd":29,"evals":29,"mlops":29,"pytorch":29,"xgboost":29,"embeddings":29,"tensorflow":29,"scikit-learn":29,"semantic search":29,"vector databases":29},[132,133,134,38,39,40,135,136,137,138,139,140],"MLOps","CI\u002FCD","scikit-learn","LLMs","RAG","Embeddings","Semantic Search","Vector Databases","Evals",{"genai":29,"monitoring":29,"ai solutions":30,"data science":30,"version control":29,"incident management":29,"root cause analysis":29},[54,143,144,145,146,147,148],"AI Solutions","GenAI","Monitoring","Incident Management","Root Cause Analysis","Version Control",{"id":150,"slug":151,"title":152,"raw_title":11,"is_featured":12,"company":153,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":156,"processed_country_iso_code_gmaps":158,"processed_home_office":20,"processed_salary_min":159,"processed_salary_max":160,"processed_salary_currency":23,"processed_salary_source":24,"processed_working_hours":161,"processed_employment_types":27,"processed_it_skills":162,"processed_it_skills_labels":164,"processed_job_expertise_skills":174,"processed_job_expertise_skills_labels":175,"max_cpc":74,"actual_cpc":74},78798,"ind-applied-ai-scientist-hartford-global-services-private-limited","IND Applied AI Scientist",{"name":154,"slug":155,"logo_url":11},"Hartford Global Services Private Limited","hartford-global-services-private-limited",[157],"Hyderabad",[19],2000000,3500000,[26],{"git":29,"sql":30,"unix":29,"numpy":30,"pandas":30,"python":30,"pytorch":29,"ratabase":163,"duck creek":163,"tensorflow":29,"aws bedrock":29,"scikit-learn":30,"aws sagemaker":29,"google vertex ai":29,"azure ai services":29},2,[32,165,166,134,33,40,39,98,167,168,169,170,171,172,173],"pandas","NumPy","Unix","Google Vertex AI","AWS SageMaker","AWS Bedrock","Azure AI Services","Duck Creek","Ratabase",{"nlp":30,"ocr":29,"rag":30,"embeddings":30,"a\u002Fb testing":30,"ai governance":29,"deep learning":30,"generative ai":30,"pii detection":29,"drift detection":30,"document parsing":29,"machine learning":30,"model deployment":30,"model evaluation":30,"model monitoring":30,"experiment design":30,"cloud ai platforms":29,"prompt engineering":30,"text normalization":29,"retrieval strategies":30,"statistical modeling":30,"production integration":30,"unstructured data processing":30},[176,108,107,177,178,179,180,181,182,183,184,185,186,187,188,137,189,190,136,191,192,193,194],"Statistical Modeling","Model Evaluation","Model Monitoring","Experiment Design","A\u002FB Testing","Drift Detection","Unstructured Data Processing","Document Parsing","OCR","Text Normalization","PII Detection","NLP","Generative AI","Retrieval Strategies","Prompt Engineering","AI Governance","Cloud AI Platforms","Model Deployment","Production Integration",{"id":196,"slug":197,"title":198,"raw_title":11,"is_featured":12,"company":199,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":200,"processed_country_iso_code_gmaps":201,"processed_home_office":20,"processed_salary_min":202,"processed_salary_max":203,"processed_salary_currency":23,"processed_salary_source":24,"processed_working_hours":204,"processed_employment_types":27,"processed_it_skills":205,"processed_it_skills_labels":206,"processed_job_expertise_skills":210,"processed_job_expertise_skills_labels":211,"max_cpc":74,"actual_cpc":74},75122,"data-scientist-refinitiv-india-shared-services-private-limited","Data Scientist",{"name":14,"slug":15,"logo_url":11},[17],[19],1500000,2500000,[26],{"r":29,"aws":29,"git":29,"sql":29,"azure":29,"mlops":29,"numpy":30,"pandas":30,"python":30,"pytorch":29,"tensorflow":29,"scikit-learn":30,"ci\u002Fcd pipelines":29},[32,207,33,208,166,37,39,40,98,209,99,100,132],"R","Pandas","CI\u002FCD pipelines",{"nlp":30,"llms":30,"statistics":30,"web scraping":29,"deep learning":30,"lseg datasets":29,"rag workflows":30,"data analytics":30,"cloud platforms":29,"coding standards":29,"entity extraction":29,"data preprocessing":29,"financial services":29,"investment banking":29,"refinitiv datasets":29,"data postprocessing":29,"feature engineering":30,"predictive modeling":30,"relational databases":30,"data management tools":29,"statistical programming":30},[212,213,214,187,135,215,216,105,217,218,219,220,221,222,223,224,225,226,227,228,229],"Data analytics","Feature engineering","Predictive modeling","RAG workflows","Deep learning","Relational databases","Statistical programming","Data management tools","Financial services","Investment banking","Refinitiv datasets","LSEG datasets","Web scraping","Entity extraction","Data preprocessing","Data postprocessing","Cloud platforms","Coding standards",{"id":231,"slug":232,"title":233,"raw_title":11,"is_featured":12,"company":234,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":237,"processed_country_iso_code_gmaps":239,"processed_home_office":20,"processed_salary_min":241,"processed_salary_max":242,"processed_salary_currency":88,"processed_salary_source":24,"processed_working_hours":243,"processed_employment_types":27,"processed_it_skills":244,"processed_it_skills_labels":245,"processed_job_expertise_skills":246,"processed_job_expertise_skills_labels":247,"max_cpc":74,"actual_cpc":74},83652,"senior-staff-applied-research-scientist-government-employees-insurance-company","Senior Staff Applied  Research Scientist",{"name":235,"slug":236,"logo_url":11},"Government Employees Insurance Company","government-employees-insurance-company",[238],"Bethesda",[240],"US",150000,300000,[26],{"sql":30,"python":30,"pytorch":30,"tensorflow":30,"scikit-learn":30},[32,33,40,39,37],{"a\u002Fb testing":30,"red-teaming":29,"deep learning":30,"prompt design":29,"kpi frameworks":30,"responsible ai":30,"data governance":30,"causal inference":30,"machine learning":30,"model deployment":30,"insurance operations":163,"statistical learning":30,"large language models":30,"numerical optimization":29,"reinforcement learning":29,"experimentation strategies":30,"human-in-the-loop workflows":29,"natural language processing":29,"retrieval-augmented generation":29},[108,107,248,249,250,180,251,252,193,253,254,255,256,257,258,259,260,261,262],"Large Language Models","Statistical Learning","Causal Inference","KPI Frameworks","Experimentation Strategies","Data Governance","Responsible AI","Numerical Optimization","Natural Language Processing","Reinforcement Learning","Retrieval-Augmented Generation","Prompt Design","Red-Teaming","Human-in-the-Loop Workflows","Insurance Operations",{"id":264,"slug":265,"title":266,"raw_title":11,"is_featured":12,"company":267,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":268,"processed_country_iso_code_gmaps":269,"processed_home_office":125,"processed_salary_min":270,"processed_salary_max":271,"processed_salary_currency":272,"processed_salary_source":24,"processed_working_hours":273,"processed_employment_types":27,"processed_it_skills":274,"processed_it_skills_labels":275,"processed_job_expertise_skills":280,"processed_job_expertise_skills_labels":281,"max_cpc":74,"actual_cpc":74},70466,"enterprise-architect-ai-and-data-bank-of-montreal","Enterprise Architect – AI and Data",{"name":80,"slug":81,"logo_url":11},[83],[85],85500,185000,"CAD",[26],{"aws":29,"gcp":29,"sql":30,"apis":29,"azure":29,"python":30,"pytorch":29,"tensorflow":29,"mlops tools":29,"microservices":29},[32,33,39,40,100,99,276,277,278,279],"GCP","MLOps tools","APIs","Microservices",{"llms":29,"generative ai":29,"ai architecture":30,"risk management":30,"data engineering":30,"machine learning":30,"data architecture":30,"cloud architecture":30,"software development":30,"technology governance":30,"reinforcement learning":29,"business case development":29,"financial industry knowledge":29,"enterprise architecture frameworks":30},[282,283,108,188,135,257,284,285,286,287,288,289,290,291],"AI Architecture","Data Architecture","Cloud Architecture","Data Engineering","Software Development","Enterprise Architecture Frameworks","Technology Governance","Risk Management","Financial Industry Knowledge","Business Case Development",{"id":293,"slug":294,"title":295,"raw_title":11,"is_featured":12,"company":296,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":297,"processed_country_iso_code_gmaps":298,"processed_home_office":20,"processed_salary_min":299,"processed_salary_max":21,"processed_salary_currency":23,"processed_salary_source":24,"processed_working_hours":300,"processed_employment_types":27,"processed_it_skills":301,"processed_it_skills_labels":302,"processed_job_expertise_skills":312,"processed_job_expertise_skills_labels":313,"max_cpc":74,"actual_cpc":74},78796,"data-ai-engineering-professionals-data-engineering-analytics-aiml-reliability-engineering-hartford-global-services-private-limited","Data & AI Engineering Professionals (Data Engineering, Analytics, AI\u002FML & Reliability Engineering)",{"name":154,"slug":155,"logo_url":11},[157],[19],800000,[26],{"aws":29,"emr":29,"gcp":29,"rag":29,"sql":29,"sre":29,"hadoop":29,"python":29,"etl\u002Felt":29,"fastapi":29,"pyspark":29,"pytorch":29,"snowflake":29,"terraform":29,"vertex ai":29,"databricks":29,"informatica":29,"scikit-learn":29},[34,303,304,305,276,99,136,306,33,32,307,308,309,94,310,37,40,311],"Snowflake","Databricks","ETL\u002FELT","Vertex AI","SRE","Informatica","EMR","FastAPI","Terraform",{"ai\u002Fml":29,"applied ai":29,"data analysis":29,"generative ai":29,"ml\u002Fai platforms":29,"data engineering":29,"data reliability":29,"machine learning":29,"big data platforms":29,"agentic ai solutions":29,"statistical modelling":29,"platform administration":29,"site reliability engineering":29},[285,314,315,316,317,318,188,319,320,321,108,322,323],"Data Analysis","Data Reliability","Big Data Platforms","Platform Administration","AI\u002FML","Agentic AI Solutions","Applied AI","Statistical Modelling","Site Reliability Engineering","ML\u002FAI Platforms",{"id":325,"slug":326,"title":327,"raw_title":11,"is_featured":12,"company":328,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":331,"processed_country_iso_code_gmaps":333,"processed_home_office":20,"processed_salary_min":21,"processed_salary_max":22,"processed_salary_currency":23,"processed_salary_source":24,"processed_working_hours":334,"processed_employment_types":27,"processed_it_skills":335,"processed_it_skills_labels":336,"processed_job_expertise_skills":339,"processed_job_expertise_skills_labels":340,"max_cpc":74,"actual_cpc":74},75324,"senior-manager-data-scientist-amvc-mg-global-services","Senior Manager - Data Scientist (AMVC)",{"name":329,"slug":330,"logo_url":11},"M&G Global Services","mg-global-services",[332],"Mumbai",[19],[26],{"sql":29,"mlops":29,"devops":29,"github":29,"pandas":30,"python":30,"pyspark":29,"pytorch":29,"databricks":29,"scikit-learn":30},[32,33,34,304,337,338,165,134,40,132],"GitHub","DevOps",{"control design":29,"data preparation":30,"machine learning":30,"model validation":30,"actuarial processes":163,"audit documentation":29,"feature engineering":30,"predictive modeling":30,"process reengineering":29,"financial data analysis":29},[65,108,341,342,343,344,345,346,347,348],"Model Validation","Feature Engineering","Data Preparation","Financial Data Analysis","Actuarial Processes","Process Reengineering","Control Design","Audit Documentation",{"id":350,"slug":351,"title":352,"raw_title":11,"is_featured":12,"company":353,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":356,"processed_country_iso_code_gmaps":358,"processed_home_office":20,"processed_salary_min":86,"processed_salary_max":360,"processed_salary_currency":361,"processed_salary_source":24,"processed_working_hours":362,"processed_employment_types":27,"processed_it_skills":363,"processed_it_skills_labels":364,"processed_job_expertise_skills":368,"processed_job_expertise_skills_labels":369,"max_cpc":74,"actual_cpc":74},69482,"global-market-risk-unit-quantitative-manager-cib-bcobilbao-vizcaya-argentaria","GLOBAL MARKET RISK UNIT QUANTITATIVE MANAGER - CIB",{"name":354,"slug":355,"logo_url":11},"BCO.BILBAO VIZCAYA ARGENTARIA","bcobilbao-vizcaya-argentaria",[357],"Bilbao",[359],"ES",120000,"EUR",[26],{"c#":30,"c++":30,"git":29,"ci\u002Fcd":29,"numpy":30,"scipy":30,"docker":29,"pandas":30,"python":30,"pytorch":30,"tensorflow":30},[32,365,366,166,367,208,40,39,98,133,95],"C++","C#","SciPy",{"xva":30,"mentoring":30,"data science":30,"machine learning":30,"derivative pricing":30,"project management":30,"market risk modeling":30,"financial engineering":30,"software architecture":30,"counterparty credit risk":30,"quantitative risk analysis":30,"regulatory frameworks (frtb, imm)":30},[370,371,54,372,373,374,375,376,108,377,378,379],"Quantitative Risk Analysis","Financial Engineering","Market Risk Modeling","Counterparty Credit Risk","XVA","Derivative Pricing","Regulatory Frameworks (FRTB, IMM)","Software Architecture","Project Management","Mentoring",{"id":381,"slug":382,"title":383,"raw_title":11,"is_featured":12,"company":384,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":385,"processed_country_iso_code_gmaps":386,"processed_home_office":125,"processed_salary_min":270,"processed_salary_max":271,"processed_salary_currency":272,"processed_salary_source":24,"processed_working_hours":387,"processed_employment_types":27,"processed_it_skills":388,"processed_it_skills_labels":389,"processed_job_expertise_skills":390,"processed_job_expertise_skills_labels":391,"max_cpc":74,"actual_cpc":74},70424,"artificial-intelligence-data-architect-developer-bank-of-montreal","Artificial Intelligence & Data Architect (Developer)",{"name":80,"slug":81,"logo_url":11},[83],[85],[26],{"aws":30,"gcp":163,"sql":29,"apis":29,"azure":163,"mlops":29,"python":30,"pytorch":29,"tensorflow":29,"microservices":29},[32,33,99,39,40,100,276,132,278,279],{"llms":29,"sdlc":30,"genai":29,"data pipelines":30,"data governance":29,"machine learning":30,"model deployment":30,"model monitoring":30,"proof-of-concept":29,"data architecture":30,"cloud architecture":30,"software development":30,"solution architecture":30,"reinforcement learning":29,"artificial intelligence":30,"enterprise architecture":30,"financial industry knowledge":29,"technical roadmap development":30},[286,283,392,108,393,394,395,396,193,178,284,144,135,257,290,253,397,398],"Artificial Intelligence","Enterprise Architecture","Solution Architecture","SDLC","Data Pipelines","Technical Roadmap Development","Proof-of-Concept",{"id":400,"slug":401,"title":402,"raw_title":11,"is_featured":12,"company":403,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":406,"processed_country_iso_code_gmaps":408,"processed_home_office":20,"processed_salary_min":360,"processed_salary_max":410,"processed_salary_currency":411,"processed_salary_source":24,"processed_working_hours":412,"processed_employment_types":27,"processed_it_skills":413,"processed_it_skills_labels":414,"processed_job_expertise_skills":416,"processed_job_expertise_skills_labels":417,"max_cpc":74,"actual_cpc":74},77322,"model-risk-management-specialist-ytl-digital-bank-berhad-registration-no-202201037182-1482879-p","Model Risk Management Specialist",{"name":404,"slug":405,"logo_url":11},"YTL Digital Bank Berhad (Registration No. 202201037182 (1482879-P))","ytl-digital-bank-berhad-registration-no-202201037182-1482879-p",[407],"Kuala Lumpur",[409],"MY",180000,"MYR",[26],{"r":30,"sas":30,"sql":30,"python":30,"pytorch":29,"tensorflow":29,"scikit-learn":29},[32,207,33,415,37,39,40],"SAS",{"stress testing":30,"bias mitigation":30,"model governance":30,"model validation":30,"credit risk modeling":30,"explainable ai (xai)":30,"financial forecasting":30,"regulatory compliance":30,"ai\u002Fml model assessment":30,"banking domain knowledge":30,"economic capital modeling":30,"aml transaction monitoring":30,"risk metrics (pd, lgd, ead)":30,"expected credit loss (mfrs9)":30,"quantitative risk management":30},[341,418,419,420,421,422,423,424,425,426,427,428,429,430,431],"Quantitative Risk Management","Credit Risk Modeling","Stress Testing","Expected Credit Loss (MFRS9)","AML Transaction Monitoring","Financial Forecasting","AI\u002FML Model Assessment","Explainable AI (XAI)","Bias Mitigation","Model Governance","Regulatory Compliance","Banking Domain Knowledge","Risk Metrics (PD, LGD, EAD)","Economic Capital Modeling",{"id":433,"slug":434,"title":435,"raw_title":11,"is_featured":12,"company":436,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":439,"processed_country_iso_code_gmaps":441,"processed_home_office":125,"processed_salary_min":126,"processed_salary_max":443,"processed_salary_currency":444,"processed_salary_source":24,"processed_working_hours":445,"processed_employment_types":27,"processed_it_skills":446,"processed_it_skills_labels":447,"processed_job_expertise_skills":449,"processed_job_expertise_skills_labels":450,"max_cpc":74,"actual_cpc":74},72163,"market-and-valuations-risk-management-valuations-specialistanalyst-associate-senior-analyst-9019-deutsche-knowledge-services-pte-ltd-manila-branch","Market and Valuations Risk Management – Valuations Specialist\u002FAnalyst - Associate \u002F Senior Analyst",{"name":437,"slug":438,"logo_url":11},"9019 Deutsche Knowledge Services Pte. Ltd., Manila Branch","9019-deutsche-knowledge-services-pte-ltd-manila-branch",[440],"Manila",[442],"PH",1200000,"PHP",[26],{"sql":29,"keras":30,"numpy":30,"pandas":30,"python":30,"pytorch":30,"tableau":29,"power bi":163,"tensorflow":30,"scikit-learn":30,"data engineering":29,"machine learning":30,"artificial intelligence":30,"cloud-based data platforms":29},[32,33,36,35,134,39,40,92,208,166,108,392,285,448],"Cloud-based data platforms",{"algorithms":29,"market risk":29,"data science":30,"control mindset":30,"data structures":29,"data visualization":29,"trading strategies":29,"quantitative finance":29,"regulatory environment":29,"valuation methodologies":29,"financial markets products":29,"software development best practices":29},[451,452,453,454,455,456,54,457,458,459,460,461],"Financial Markets Products","Valuation Methodologies","Market Risk","Trading Strategies","Regulatory Environment","Control Mindset","Quantitative Finance","Data Structures","Algorithms","Software Development Best Practices","Data Visualization",{"id":463,"slug":464,"title":465,"raw_title":11,"is_featured":12,"company":466,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":467,"processed_country_iso_code_gmaps":468,"processed_home_office":125,"processed_salary_min":469,"processed_salary_max":470,"processed_salary_currency":444,"processed_salary_source":24,"processed_working_hours":471,"processed_employment_types":27,"processed_it_skills":472,"processed_it_skills_labels":473,"processed_job_expertise_skills":474,"processed_job_expertise_skills_labels":475,"max_cpc":74,"actual_cpc":74},82983,"market-and-valuation-risk-management-valuations-senior-specialist-avp-9019-deutsche-knowledge-services-pte-ltd-manila-branch","Market and Valuation Risk Management – Valuations Senior Specialist - AVP",{"name":437,"slug":438,"logo_url":11},[440],[442],60000,90000,[26],{"sql":29,"keras":30,"numpy":30,"pandas":30,"python":30,"pytorch":30,"tableau":29,"power bi":29,"tensorflow":30,"scikit-learn":30,"cloud-based data platforms":29},[32,33,36,35,134,39,40,92,208,166,448],{"data analytics":29,"control mindset":30,"data engineering":29,"machine learning":30,"market risk management":30,"artificial intelligence":30,"valuation methodologies":30,"data structures and algorithms":29,"software development best practices":29,"financial markets products knowledge":30},[476,477,478,479,212,480,481,482,483,484],"Financial markets products knowledge","Valuation methodologies","Market risk management","Control mindset","Machine learning","Artificial intelligence","Data engineering","Software development best practices","Data structures and algorithms",{"id":486,"slug":487,"title":488,"raw_title":11,"is_featured":12,"company":489,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":490,"processed_country_iso_code_gmaps":491,"processed_home_office":125,"processed_salary_min":203,"processed_salary_max":492,"processed_salary_currency":23,"processed_salary_source":24,"processed_working_hours":493,"processed_employment_types":27,"processed_it_skills":494,"processed_it_skills_labels":495,"processed_job_expertise_skills":525,"processed_job_expertise_skills_labels":526,"max_cpc":74,"actual_cpc":74},78821,"ind-senior-engineer-data-hartford-global-services-private-limited","IND Senior Engineer, Data",{"name":154,"slug":155,"logo_url":11},[157],[19],4000000,[26],{"a2a":30,"aws":30,"mcp":30,"rdf":30,"sql":30,"azure":30,"ci\u002Fcd":30,"neo4j":30,"nosql":30,"spark":30,"aws s3":30,"cypher":30,"docker":30,"python":30,"sparql":30,"aws ec2":30,"mongodb":30,"pytorch":29,"big data":30,"dynamodb":30,"data lake":30,"data mesh":30,"langchain":30,"langgraph":30,"snowflake":30,"aws lambda":30,"kubernetes":30,"tensorflow":29,"aws kinesis":30,"data fabric":30,"apache kafka":30,"document dbs":30,"etl\u002Felt tools":30,"gcp vertex ai":30,"spanner graph":30,"amazon neptune":30,"aws opensearch":30,"graph databases":30,"spark streaming":30,"vector databases":30,"google cloud platform":30},[496,497,498,33,499,303,500,133,501,99,101,100,32,502,503,504,505,95,96,40,39,139,506,507,508,509,510,511,512,513,514,515,516,517,518,519,520,521,522,523,524],"Apache Kafka","AWS Kinesis","Spark Streaming","NoSQL","ETL\u002FELT tools","Big Data","Spark","Data Mesh","Data Lake","Data Fabric","Graph Databases","Document DBs","AWS OpenSearch","GCP Vertex AI","Neo4j","Spanner Graph","Amazon Neptune","MongoDB","DynamoDB","AWS Lambda","AWS S3","AWS EC2","LangChain","LangGraph","MCP","A2A","Cypher","SPARQL","RDF",{"devops":30,"data lakes":30,"data domains":30,"data lineage":30,"data quality":30,"scaled agile":30,"data products":30,"generative ai":30,"data catalogue":30,"data governance":30,"cloud technology":30,"data engineering":30,"data integration":30,"data warehousing":30,"knowledge graphs":30,"data architecture":30,"semantic modeling":30,"prompt engineering":30,"business intelligence":30,"reliability engineering":30,"synthetic data generation":30,"ai-driven data engineering":30,"insurance domain knowledge":29,"retrieval-augmented generation (rag)":30},[285,283,527,528,529,530,531,532,533,188,534,190,535,536,537,253,538,539,540,541,338,542,543,544],"Data Warehousing","Data Integration","Data Lakes","Data Domains","Data Products","Business Intelligence","Cloud Technology","Retrieval-Augmented Generation (RAG)","Semantic Modeling","Knowledge Graphs","Synthetic Data Generation","Data Quality","Data Lineage","Data Catalogue","AI-driven Data Engineering","Reliability Engineering","Scaled Agile","Insurance Domain Knowledge",{"id":546,"slug":547,"title":548,"raw_title":11,"is_featured":12,"company":549,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":550,"processed_country_iso_code_gmaps":552,"processed_home_office":125,"processed_salary_min":469,"processed_salary_max":470,"processed_salary_currency":361,"processed_salary_source":24,"processed_working_hours":553,"processed_employment_types":27,"processed_it_skills":554,"processed_it_skills_labels":555,"processed_job_expertise_skills":558,"processed_job_expertise_skills_labels":559,"max_cpc":74,"actual_cpc":74},69476,"data-scientist-genai-llms-bcobilbao-vizcaya-argentaria","Data Scientist GenAI (LLMs)",{"name":354,"slug":355,"logo_url":11},[551],"Madrid",[359],[26],{"aws":163,"azure":163,"numpy":30,"docker":163,"pandas":30,"python":30,"pyspark":29,"pytorch":29,"langchain":163,"langgraph":163,"kubernetes":163,"tensorflow":29,"google cloud":163,"scikit-learn":30,"huggingface transformers":29},[32,208,166,134,34,39,40,556,518,519,99,557,100,95,96],"HuggingFace Transformers","Google Cloud",{"ethical ai":29,"a\u002Fb testing":29,"data analysis":30,"cloud computing":163,"causal inference":163,"fine-tuning llms":30,"machine learning":30,"ai risk assessment":30,"model optimization":30,"prompt engineering":30,"statistical modeling":30,"embedding elicitation":30,"data lifecycle management":30,"large language models (llms)":30,"data privacy laws (gdpr, ccpa)":29},[176,108,560,561,190,562,563,314,564,565,180,566,567,250,568],"Large Language Models (LLMs)","Fine-tuning LLMs","Embedding Elicitation","Model Optimization","Data Lifecycle Management","AI Risk Assessment","Ethical AI","Data Privacy Laws (GDPR, CCPA)","Cloud Computing",{"id":570,"slug":571,"title":572,"raw_title":11,"is_featured":12,"company":573,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":574,"processed_country_iso_code_gmaps":575,"processed_home_office":20,"processed_salary_min":159,"processed_salary_max":160,"processed_salary_currency":23,"processed_salary_source":24,"processed_working_hours":576,"processed_employment_types":27,"processed_it_skills":577,"processed_it_skills_labels":578,"processed_job_expertise_skills":591,"processed_job_expertise_skills_labels":592,"max_cpc":74,"actual_cpc":74},78804,"ind-lead-software-engineer-hartford-global-services-private-limited-4","IND Lead Software Engineer",{"name":154,"slug":155,"logo_url":11},[157],[19],[26],{"a2a":29,"adk":29,"mcp":29,"nexus":163,"numpy":29,"crewai":29,"github":29,"pandas":29,"python":30,"airflow":163,"asyncio":29,"fastapi":29,"pytorch":29,"mcp-scan":163,"pydantic":29,"checkmarx":163,"langchain":29,"langgraph":29,"snowflake":163,"sonarqube":163,"terraform":29,"aws bedrock":29,"hugging face":29,"aws sagemaker":29,"opentelemetry":29,"apache iceberg":163,"google vertex ai":29},[32,40,579,208,166,169,170,168,311,337,580,581,582,583,303,584,585,586,310,587,588,518,519,589,590,521,520],"Hugging Face","Nexus","SonarQube","Checkmarx","mcp-scan","Airflow","Apache Iceberg","OpenTelemetry","Pydantic","asyncio","CrewAI","ADK",{"hyde":29,"safe":29,"ci\u002Fcd":29,"mlops":30,"devops":29,"raptor":29,"pub\u002Fsub":29,"graphrag":29,"devsecops":29,"agentic ai":30,"agentic rag":30,"rag systems":30,"generative ai":30,"microservices":29,"observability":29,"data pipelines":163,"ml engineering":30,"api development":29,"bias mitigation":163,"drift monitoring":29,"llm architecture":30,"model evaluation":29,"automated testing":163,"adaptive prompting":29,"canary deployments":163,"agile methodologies":29,"context engineering":29,"distributed systems":29,"rollback strategies":163,"counterfactual testing":163,"infrastructure as code":29,"multi-agent coordination":29,"disparate impact analysis":163,"event-driven architecture":29,"point-to-point architecture":29},[593,132,594,188,595,596,597,598,599,600,601,602,603,338,133,604,605,606,607,608,609,610,611,612,279,177,613,614,615,616,617,396,426,618,619],"ML Engineering","LLM Architecture","Agentic AI","RAG Systems","Agentic RAG","Context Engineering","Adaptive Prompting","Multi-agent Coordination","HyDE","RAPTOR","GraphRAG","Infrastructure as Code","DevSecOps","Agile Methodologies","SAFe","Distributed Systems","Event-driven Architecture","Pub\u002FSub","Point-to-point Architecture","API Development","Observability","Drift Monitoring","Automated Testing","Canary Deployments","Rollback Strategies","Disparate Impact Analysis","Counterfactual Testing",{"id":621,"slug":622,"title":198,"raw_title":11,"is_featured":12,"company":623,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":626,"processed_country_iso_code_gmaps":627,"processed_home_office":20,"processed_salary_min":360,"processed_salary_max":410,"processed_salary_currency":411,"processed_salary_source":24,"processed_working_hours":628,"processed_employment_types":27,"processed_it_skills":629,"processed_it_skills_labels":630,"processed_job_expertise_skills":631,"processed_job_expertise_skills_labels":632,"max_cpc":74,"actual_cpc":74},76395,"data-scientist-ocbc-malaysia-2",{"name":624,"slug":625,"logo_url":11},"OCBC Malaysia","ocbc-malaysia",[407],[409],[26],{"sql":29,"hadoop":163,"python":30,"pytorch":29,"tensorflow":29,"apache spark":163,"scikit-learn":29},[32,39,40,134,33,94,93],{"mentoring":30,"data science":30,"data analysis":30,"deep learning":29,"generative ai":30,"team leadership":30,"machine learning":30,"data visualization":29,"big data technologies":163,"ai solution deployment":30,"reinforcement learning":29,"strategic decision making":30,"natural language processing":29},[54,188,108,107,256,257,633,634,635,379,314,461,636],"Big Data Technologies","AI Solution Deployment","Team Leadership","Strategic Decision Making",{"id":638,"slug":639,"title":640,"raw_title":11,"is_featured":12,"company":641,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":642,"processed_country_iso_code_gmaps":643,"processed_home_office":125,"processed_salary_min":644,"processed_salary_max":360,"processed_salary_currency":361,"processed_salary_source":24,"processed_working_hours":645,"processed_employment_types":27,"processed_it_skills":646,"processed_it_skills_labels":647,"processed_job_expertise_skills":663,"processed_job_expertise_skills_labels":664,"max_cpc":74,"actual_cpc":74},69486,"senior-data-scientist-foundation-model-ai-factory-bcobilbao-vizcaya-argentaria","Senior Data Scientist - Foundation Model - AI Factory",{"name":354,"slug":355,"logo_url":11},[357],[359],70000,[26],{"lora":29,"python":30,"pytorch":30,"checkpointing":29,"experiment tracking":29,"memory optimization":29,"sequential modeling":30,"distributed training":30,"performance profiling":29,"optimization algorithms":30,"representation learning":30,"mixed precision training":29,"transformer architectures":30,"graph neural networks (gnn)":29,"software engineering practices":30,"parameter-efficient fine-tuning":29,"large language model (llm) pre-training":30},[32,40,648,649,650,651,652,653,654,655,656,657,658,659,660,661,662],"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":30,"responsible ai":30,"risk management":29,"data preparation":30,"machine learning":30,"model evaluation":30,"scalable ai systems":30,"production deployment":30,"regulatory compliance":29,"financial data analysis":29,"research and development":30,"model architecture design":30},[108,107,665,343,177,666,344,289,428,667,668,254],"Model Architecture Design","Production Deployment","Research and Development","Scalable AI Systems",{"id":670,"slug":671,"title":672,"raw_title":11,"is_featured":12,"company":673,"raw_hiringOrganization_logo_url":11,"processed_city_gmaps":676,"processed_country_iso_code_gmaps":678,"processed_home_office":125,"processed_salary_min":644,"processed_salary_max":680,"processed_salary_currency":681,"processed_salary_source":24,"processed_working_hours":682,"processed_employment_types":27,"processed_it_skills":683,"processed_it_skills_labels":684,"processed_job_expertise_skills":690,"processed_job_expertise_skills_labels":691,"max_cpc":74,"actual_cpc":697},71537,"ml-ops-engineer-cmc-markets-uk-plc-2","ML Ops Engineer",{"name":674,"slug":675,"logo_url":11},"CMC Markets UK Plc","cmc-markets-uk-plc",[677],"London",[679],"GB",100000,"GBP",[26],{"ci\u002Fcd":30,"docker":30,"python":30,"pytorch":29,"kubernetes":29,"feature store":29,"model serving":30,"model registry":29,"cloud computing":30,"observability tools":30,"infrastructure as code":29,"ml workflow orchestration":30},[32,40,133,95,96,604,568,685,686,687,688,689],"Model Serving","ML Workflow Orchestration","Observability Tools","Model Registry","Feature Store",{"mlops":30,"system design":30,"model deployment":30,"model monitoring":30,"cost optimization":29,"incident response":30,"security compliance":29,"ml lifecycle management":30,"reliability engineering":30},[132,692,193,178,693,694,542,695,696],"ML Lifecycle Management","Incident Response","System Design","Security Compliance","Cost Optimization",0.5,{"industry":699,"employment_type":745,"expertise_skills":755,"it_skills":824,"salary_currency":892,"processed_working_hours":910},[700,704,708,712,716,720,724,727,730,733,736,739,742],{"key":701,"label":702,"count":703},"financial services","Financial Services",33,{"key":705,"label":706,"count":707},"insurance","Insurance",27,{"key":709,"label":710,"count":711},"banking","Banking",18,{"key":713,"label":714,"count":715},"financial markets infrastructure","Financial Markets Infrastructure",15,{"key":717,"label":718,"count":719},"data","Data",9,{"key":721,"label":722,"count":723},"data provider","Data Provider",6,{"key":725,"label":726,"count":30},"asset management","Asset Management",{"key":728,"label":729,"count":163},"private equity","Private Equity",{"key":731,"label":732,"count":163},"wealth management","Wealth Management",{"key":734,"label":735,"count":74},"management","Management",{"key":737,"label":738,"count":74},"technology services for financial institutions","Technology Services For Financial Institutions",{"key":740,"label":741,"count":74},"fund administration","Fund Administration",{"key":743,"label":744,"count":74},"middle office","Middle Office",[746,749,752],{"key":27,"label":747,"count":748},"PERMANENT",84,{"key":750,"label":751,"count":163},"student","STUDENT",{"key":753,"label":754,"count":74},"contract","CONTRACT",[756,759,762,766,769,771,775,778,780,782,785,789,792,796,799,801,804,807,810,812,814,816,819,822],{"key":757,"label":108,"slug":757,"count":758},"machine-learning",53,{"key":760,"label":107,"slug":760,"count":761},"deep-learning",32,{"key":763,"label":764,"slug":763,"count":765},"generative-ai","Generative Ai",20,{"key":767,"label":190,"slug":767,"count":768},"prompt-engineering",19,{"key":770,"label":256,"slug":770,"count":711},"natural-language-processing",{"key":772,"label":773,"slug":772,"count":774},"mlops","Mlops",17,{"key":776,"label":342,"slug":776,"count":777},"feature-engineering",16,{"key":779,"label":177,"slug":779,"count":777},"model-evaluation",{"key":781,"label":285,"slug":781,"count":715},"data-engineering",{"key":783,"label":54,"slug":783,"count":784},"data-science",14,{"key":786,"label":787,"slug":786,"count":788},"nlp","Nlp",13,{"key":790,"label":193,"slug":790,"count":791},"model-deployment",12,{"key":793,"label":794,"slug":793,"count":795},"ai-governance","Ai Governance",11,{"key":797,"label":105,"slug":797,"count":798},"statistics",10,{"key":800,"label":178,"slug":800,"count":798},"model-monitoring",{"key":802,"label":803,"slug":802,"count":798},"responsible-ai","Responsible Ai",{"key":805,"label":806,"slug":805,"count":798},"data-analytics","Data Analytics",{"key":808,"label":809,"slug":808,"count":798},"llms","Llms",{"key":811,"label":257,"slug":811,"count":719},"reinforcement-learning",{"key":813,"label":253,"slug":813,"count":719},"data-governance",{"key":815,"label":568,"slug":815,"count":719},"cloud-computing",{"key":817,"label":818,"slug":817,"count":719},"rag","Rag",{"key":820,"label":608,"slug":820,"count":821},"distributed-systems",8,{"key":823,"label":248,"slug":823,"count":821},"large-language-models",[825,828,831,835,838,841,845,849,853,856,860,862,864,866,869,872,875,877,878,880,883,885,887,890],{"key":826,"label":827,"slug":826,"count":5},"pytorch","Pytorch",{"key":829,"label":32,"slug":829,"count":830},"python",85,{"key":832,"label":833,"slug":832,"count":834},"tensorflow","Tensorflow",73,{"key":836,"label":33,"slug":836,"count":837},"sql",60,{"key":134,"label":839,"slug":134,"count":840},"Scikit-Learn",48,{"key":842,"label":843,"slug":842,"count":844},"aws","Aws",40,{"key":846,"label":847,"slug":846,"count":848},"ms-azure","MS Azure",36,{"key":850,"label":851,"slug":850,"count":852},"cicd","Ci\u002FCd",26,{"key":854,"label":96,"slug":854,"count":855},"kubernetes",23,{"key":857,"label":858,"slug":857,"count":859},"langchain","Langchain",22,{"key":861,"label":95,"slug":861,"count":859},"docker",{"key":863,"label":98,"slug":863,"count":859},"git",{"key":165,"label":208,"slug":165,"count":865},21,{"key":867,"label":868,"slug":867,"count":768},"numpy","Numpy",{"key":870,"label":871,"slug":870,"count":715},"gcp","Gcp",{"key":873,"label":874,"slug":873,"count":784},"java","Java",{"key":876,"label":303,"slug":876,"count":784},"snowflake",{"key":772,"label":773,"slug":772,"count":788},{"key":879,"label":207,"slug":879,"count":791},"r",{"key":881,"label":882,"slug":881,"count":798},"langgraph","Langgraph",{"key":884,"label":579,"slug":884,"count":798},"hugging-face",{"key":886,"label":365,"slug":886,"count":798},"c",{"key":888,"label":889,"slug":888,"count":798},"aws-sagemaker","Aws Sagemaker",{"key":891,"label":502,"slug":891,"count":719},"spark",[893,894,895,896,898,899,901,902,903,905,906,908],{"key":88,"label":88,"count":855},{"key":23,"label":23,"count":768},{"key":361,"label":361,"count":795},{"key":897,"label":897,"count":798},"SGD",{"key":272,"label":272,"count":821},{"key":444,"label":444,"count":900},5,{"key":681,"label":681,"count":30},{"key":411,"label":411,"count":163},{"key":904,"label":904,"count":163},"PLN",{"key":128,"label":128,"count":74},{"key":907,"label":907,"count":74},"HKD",{"key":909,"label":909,"count":74},"CNY",[911,913],{"key":26,"label":26,"count":912},86,{"key":914,"label":914,"count":74},"PART_TIME",{"total":74,"jobs":916},[]]