[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"seo-content-expertise-model-governance-sg":3,"job-search-\u002Fen-sg\u002Fjobs-by-expertise\u002Fmodel-governance":20,"expertise-filters-\u002Fen-sg\u002Fjobs-by-expertise\u002Fmodel-governance":253,"featured-jobs-\u002Fen-sg\u002Fjobs-by-expertise\u002Fmodel-governance":378},{"image_path":4,"content_de":4,"content_en":5,"composite_key":18,"last_updated":19},null,{"tab1":6,"tab2":9,"tab3":12,"tab4":15},{"title":7,"content":8},"Strategic Importance","In Singapore's rapidly evolving financial landscape, Model Governance has emerged as a cornerstone of risk management and regulatory compliance. With the increasing reliance on complex models for credit scoring, fraud detection, and investment strategies, the demand for professionals who can ensure model accuracy, transparency, and accountability is soaring. Currently, there are 7 open positions in Singapore, reflecting the critical role this expertise plays in safeguarding financial stability. Model Governance professionals are essential in mitigating risks associated with model misuse, data bias, and regulatory penalties. They work closely with cross-functional teams to establish robust frameworks that align with both local and international standards. Beyond technical proficiency, this role requires a deep understanding of [Machine Learning](\u002Fen-sg\u002Fjobs-by-expertise\u002Fmachine-learning), [Project Management](\u002Fen-sg\u002Fjobs-by-expertise\u002Fproject-management), [Regulatory Compliance](\u002Fen-sg\u002Fjobs-by-expertise\u002Fregulatory-compliance), enabling professionals to navigate the intricate interplay between business objectives and regulatory expectations. As Singapore solidifies its position as a global fintech hub, the strategic importance of Model Governance cannot be overstated—it is the bedrock upon which trust in financial systems is built.",{"title":10,"content":11},"Top Industries & Locations","Model Governance roles in Singapore are predominantly concentrated in key financial hubs, with [Singapore](\u002Fen-sg\u002Fjobs-in-singapore) emerging as the primary hotspots. These locations host a dense cluster of financial institutions, regulatory bodies, and technology firms, creating a vibrant ecosystem for Model Governance professionals. The demand spans across a diverse range of industries, including [Banking](\u002Fen-sg\u002Fjobs-by-industry\u002Fbanking), [Financial Services](\u002Fen-sg\u002Fjobs-by-industry\u002Ffinancial-services), each requiring tailored governance frameworks to address unique model risks. For instance, banking and financial services rely heavily on credit risk models, while insurance companies focus on actuarial and claims models. Asset and wealth management firms prioritize investment performance models, and fintech companies emphasize algorithmic trading and credit scoring models. This cross-industry applicability ensures that Model Governance experts have ample opportunities to specialize and grow. Moreover, the presence of regulatory authorities in these locations fosters a culture of compliance, making them ideal for professionals seeking to make a tangible impact. Whether you are an experienced practitioner or an aspiring analyst, the geographical concentration of opportunities in [Singapore](\u002Fen-sg\u002Fjobs-in-singapore) offers a promising career trajectory in Model Governance.",{"title":13,"content":14},"In-Demand Skills & Employers","To excel in Model Governance in Singapore, professionals must possess a blend of technical and analytical skills. The most sought-after competencies include [Python](\u002Fen-sg\u002Fjobs-by-skill\u002Fpython), [Sql](\u002Fen-sg\u002Fjobs-by-skill\u002Fsql), [Hive](\u002Fen-sg\u002Fjobs-by-skill\u002Fhive), which are essential for developing, validating, and monitoring models. Proficiency in these tools enables professionals to conduct thorough model testing, performance tracking, and risk assessment. Additionally, a strong foundation in statistical analysis and machine learning is increasingly valuable, as models become more sophisticated. Leading employers in this domain, such as [United Overseas Bank Ltd](\u002Fen-sg\u002Fcompany\u002Funited-overseas-bank-ltd), [OCBC Bank](\u002Fen-sg\u002Fcompany\u002Focbc-bank), are actively seeking candidates who can demonstrate a robust understanding of model risk management frameworks and regulatory guidelines. These organizations offer competitive compensation packages and opportunities for professional growth. They value individuals who can communicate complex model concepts to non-technical stakeholders, ensuring alignment with business strategies. Furthermore, certifications in risk management and data analytics can significantly enhance your marketability. As the demand for Model Governance expertise continues to rise, staying abreast of emerging technologies and regulatory changes is crucial for career advancement.",{"title":16,"content":17},"Career Path & Salary","A career in Model Governance in Singapore offers a rewarding trajectory with competitive remuneration. Entry-level positions typically start at SGD 90k, while experienced professionals can earn up to SGD 250k. The median salary stands at SGD 180k, with the interquartile range (SGD 180k – SGD 215k) reflecting the variance based on experience, industry, and company size. With 7 open positions, the job market is robust, providing ample opportunities for both junior and senior roles. Career progression often follows a path from Model Risk Analyst to Model Governance Manager, and eventually to Director of Model Risk Management. Along the way, professionals can expect to take on greater responsibilities, such as leading validation teams, developing governance policies, and liaising with regulators. Continuous learning is vital, as the field evolves with advancements in AI and machine learning. Professionals who invest in upskilling and networking can accelerate their career growth and command higher salaries. Overall, Model Governance offers a stable and lucrative career path for those passionate about risk and compliance in the financial sector.","expertise:model-governance:sg","2026-08-17T19:49:00.477083+02:00",{"total":21,"jobs":22},7,[23,85,108,149,171,211,229],{"id":24,"slug":25,"title":26,"raw_title":4,"is_featured":27,"company":28,"raw_hiringOrganization_logo_url":4,"processed_city_gmaps":31,"processed_country_iso_code_gmaps":33,"processed_home_office":35,"processed_salary_min":36,"processed_salary_max":37,"processed_salary_currency":38,"processed_salary_source":39,"processed_working_hours":40,"processed_employment_types":42,"processed_it_skills":43,"processed_it_skills_labels":46,"processed_job_expertise_skills":57,"processed_job_expertise_skills_labels":58,"max_cpc":84,"actual_cpc":84},79284,"vice-president-fraud-data-analytics-group-compliance-united-overseas-bank-ltd","Vice President, Fraud Data Analytics, Group Compliance",false,{"name":29,"slug":30,"logo_url":4},"United Overseas Bank Ltd","united-overseas-bank-ltd",[32],"Singapore",[34],"SG","onsite",150000,250000,"SGD","estimated",[41],"FULL_TIME","permanent",{"hive":44,"keras":44,"spark":44,"impala":44,"pandas":45,"python":45,"tensorflow":44,"scikit-learn":44,"network link analysis":44,"natural language processing":44},3,4,[47,48,49,50,51,52,53,54,55,56],"Python","Hive","Spark","Impala","Pandas","Keras","TensorFlow","Scikit-learn","Natural Language Processing","Network Link Analysis",{"data science":45,"model testing":45,"data wrangling":45,"model training":45,"fraud analytics":45,"fraud detection":45,"model selection":45,"structured data":45,"machine learning":45,"model governance":44,"feature selection":45,"model development":45,"rule-based models":44,"supervised models":45,"unstructured data":45,"big data analytics":45,"project management":44,"unsupervised models":45,"semi-structured data":44,"distributed databases":44,"regulatory compliance":44,"exploratory data analysis":45,"financial crime analytics":45,"financial crime compliance":45,"analytical model development":45},[59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83],"Fraud Detection","Financial Crime Compliance","Data Science","Machine Learning","Model Development","Model Governance","Big Data Analytics","Data Wrangling","Exploratory Data Analysis","Feature Selection","Model Selection","Model Training","Model Testing","Rule-based Models","Supervised Models","Unsupervised Models","Structured Data","Unstructured Data","Semi-structured Data","Distributed Databases","Analytical Model Development","Fraud Analytics","Financial Crime Analytics","Regulatory Compliance","Project Management",1,{"id":86,"slug":87,"title":88,"raw_title":4,"is_featured":27,"company":89,"raw_hiringOrganization_logo_url":4,"processed_city_gmaps":90,"processed_country_iso_code_gmaps":91,"processed_home_office":35,"processed_salary_min":92,"processed_salary_max":93,"processed_salary_currency":38,"processed_salary_source":39,"processed_working_hours":94,"processed_employment_types":42,"processed_it_skills":95,"processed_it_skills_labels":96,"processed_job_expertise_skills":103,"processed_job_expertise_skills_labels":104,"max_cpc":84,"actual_cpc":84},79285,"vice-president-data-scientist-group-retail-united-overseas-bank-ltd","Vice President, Data Scientist, Group Retail",{"name":29,"slug":30,"logo_url":4},[32],[34],120000,180000,[41],{"r":45,"sas":45,"sql":45,"qlik":44,"keras":45,"pandas":45,"python":45,"tableau":44,"power bi":44,"tensorflow":45,"scikit-learn":45},[97,47,98,99,51,52,53,54,100,101,102],"SQL","R","SAS","Qlik","Power BI","Tableau",{"data science":45,"model testing":45,"data wrangling":45,"model training":45,"model selection":45,"machine learning":45,"model governance":44,"feature selection":45,"data visualization":45,"distributed databases":44,"network link analysis":44,"exploratory data analysis":45,"financial crime risk (fcr)":44,"anti-money laundering (aml)":44,"natural language processing":44},[61,62,66,67,68,69,70,71,64,105,106,107,55,56,78],"Anti-Money Laundering (AML)","Financial Crime Risk (FCR)","Data Visualization",{"id":109,"slug":110,"title":111,"raw_title":4,"is_featured":27,"company":112,"raw_hiringOrganization_logo_url":4,"processed_city_gmaps":113,"processed_country_iso_code_gmaps":114,"processed_home_office":35,"processed_salary_min":92,"processed_salary_max":93,"processed_salary_currency":38,"processed_salary_source":39,"processed_working_hours":115,"processed_employment_types":42,"processed_it_skills":116,"processed_it_skills_labels":117,"processed_job_expertise_skills":132,"processed_job_expertise_skills_labels":133,"max_cpc":84,"actual_cpc":84},68049,"vp-system-analyst-data-group-technology-amp-ops-1011-united-overseas-bank-ltd","VP, System Analyst (Data), Group Technology & Ops",{"name":29,"slug":30,"logo_url":4},[32],[34],[41],{"sql":45,"hive":44,"numpy":45,"spark":45,"pandas":45,"python":45,"power bi":44,"qliksense":44,"snowflake":45,"databricks":45,"delta lake":45,"apache hudi":44,"azure fabric":45,"trino\u002Fpresto":44,"apache iceberg":45,"google bigquery":45,"informatica bdm":44,"informatica idq":44,"informatica powercenter":44,"informatica enterprise data catalogue":44},[97,47,118,119,120,121,122,123,124,49,125,48,101,126,127,128,129,130,51,131],"Databricks","Snowflake","Azure Fabric","Google BigQuery","Apache Iceberg","Delta Lake","Apache Hudi","Trino\u002FPresto","QlikSense","Informatica PowerCenter","Informatica BDM","Informatica IDQ","Informatica Enterprise Data Catalogue","NumPy",{"nlp":45,"data lineage":45,"data quality":45,"data modeling":45,"data governance":45,"knowledge graph":44,"solution design":45,"data integration":45,"machine learning":45,"model governance":45,"cost optimization":44,"data architecture":45,"campaign analytics":44,"performance tuning":44,"project management":45,"credit risk analytics":45,"regulatory compliance":45,"requirements analysis":45,"rule-based decisioning":45},[134,135,62,136,137,138,82,83,139,140,141,142,64,143,144,145,146,147,148],"Data Architecture","Data Governance","NLP","Credit Risk Analytics","Campaign Analytics","Requirements Analysis","Solution Design","Data Quality","Data Lineage","Knowledge Graph","Rule-Based Decisioning","Data Integration","Data Modeling","Cost Optimization","Performance Tuning",{"id":150,"slug":151,"title":152,"raw_title":4,"is_featured":27,"company":153,"raw_hiringOrganization_logo_url":4,"processed_city_gmaps":154,"processed_country_iso_code_gmaps":155,"processed_home_office":35,"processed_salary_min":36,"processed_salary_max":37,"processed_salary_currency":38,"processed_salary_source":39,"processed_working_hours":156,"processed_employment_types":42,"processed_it_skills":157,"processed_it_skills_labels":158,"processed_job_expertise_skills":162,"processed_job_expertise_skills_labels":163,"max_cpc":84,"actual_cpc":84},68041,"senior-vp-transaction-monitoring-systems-head-compliance-analytics-amp-insights-group-compliance-1011-united-overseas-bank-ltd","Senior VP - Transaction Monitoring Systems Head, Compliance Analytics & Insights, Group Compliance",{"name":29,"slug":30,"logo_url":4},[32],[34],[41],{"dashboards":44,"data analysis":45,"machine learning":44,"statistical concepts":44},[159,62,160,161],"Data Analysis","Statistical Concepts","Dashboards",{"model governance":44,"project management":45,"programme management":45,"regulatory compliance":45,"threshold calibration":45,"alert quality management":45,"data science integration":44,"false positive reduction":45,"aml transaction monitoring":45,"scenario design and optimization":45},[164,165,166,167,168,169,83,82,64,170],"AML Transaction Monitoring","Scenario Design and Optimization","Threshold Calibration","Alert Quality Management","False Positive Reduction","Programme Management","Data Science Integration",{"id":172,"slug":173,"title":174,"raw_title":4,"is_featured":27,"company":175,"raw_hiringOrganization_logo_url":4,"processed_city_gmaps":178,"processed_country_iso_code_gmaps":179,"processed_home_office":35,"processed_salary_min":92,"processed_salary_max":93,"processed_salary_currency":38,"processed_salary_source":39,"processed_working_hours":180,"processed_employment_types":42,"processed_it_skills":181,"processed_it_skills_labels":183,"processed_job_expertise_skills":196,"processed_job_expertise_skills_labels":197,"max_cpc":84,"actual_cpc":84},62501,"senior-applied-data-scientist-ocbc-bank","Senior Applied Data Scientist",{"name":176,"slug":177,"logo_url":4},"OCBC Bank","ocbc-bank",[],[34],[41],{"aws":44,"git":44,"ray":44,"sql":44,"jira":44,"trino":44,"hadoop":44,"python":45,"elastic":44,"jenkins":44,"microsoft word":182,"microsoft excel":44,"microsoft access":182,"microsoft powerpoint":182},2,[47,97,184,185,186,187,188,189,190,191,192,193,194,195],"Hadoop","Trino","Elastic","Ray","AWS","Git","Jenkins","Jira","Microsoft Excel","Microsoft Access","Microsoft Word","Microsoft PowerPoint",{"ci\u002Fcd":44,"mlops":45,"data science":45,"deep learning":45,"generative ai":45,"responsible ai":44,"fraud detection":44,"risk management":44,"data engineering":44,"machine learning":45,"model deployment":45,"model governance":44,"model monitoring":45,"customer analytics":45,"project management":44,"statistical modeling":45,"large language models":45,"retrieval-augmented generation":45},[61,62,198,199,200,201,202,59,203,204,205,206,207,208,209,64,210,83],"Deep Learning","Generative AI","Statistical Modeling","Customer Analytics","Risk Management","Model Deployment","MLOps","CI\u002FCD","Data Engineering","Large Language Models","Retrieval-Augmented Generation","Model Monitoring","Responsible AI",{"id":212,"slug":213,"title":214,"raw_title":4,"is_featured":27,"company":215,"raw_hiringOrganization_logo_url":4,"processed_city_gmaps":216,"processed_country_iso_code_gmaps":217,"processed_home_office":35,"processed_salary_min":218,"processed_salary_max":219,"processed_salary_currency":38,"processed_salary_source":39,"processed_working_hours":220,"processed_employment_types":42,"processed_it_skills":221,"processed_it_skills_labels":222,"processed_job_expertise_skills":225,"processed_job_expertise_skills_labels":226,"max_cpc":84,"actual_cpc":84},62249,"avp-credit-risk-data-scientist-credit-risk-modelling-ocbc-bank","AVP, Credit Risk Data Scientist, Credit Risk Modelling",{"name":176,"slug":177,"logo_url":4},[],[34],90000,130000,[41],{"git":182,"sql":44,"hive":44,"jira":182,"spark":44,"trino":44,"hadoop":44,"python":45,"jenkins":182,"pytorch":45,"tensorflow":45,"scikit-learn":45},[47,97,184,48,185,49,191,190,189,223,53,224],"Scikit-Learn","PyTorch",{"data analysis":45,"risk management":45,"machine learning":45,"model governance":44,"model validation":44,"project management":44,"credit risk modelling":45,"regulatory compliance":44},[227,62,159,228,64,82,202,83],"Credit Risk Modelling","Model Validation",{"id":230,"slug":231,"title":232,"raw_title":4,"is_featured":27,"company":233,"raw_hiringOrganization_logo_url":4,"processed_city_gmaps":234,"processed_country_iso_code_gmaps":235,"processed_home_office":35,"processed_salary_min":92,"processed_salary_max":93,"processed_salary_currency":38,"processed_salary_source":39,"processed_working_hours":236,"processed_employment_types":42,"processed_it_skills":237,"processed_it_skills_labels":238,"processed_job_expertise_skills":240,"processed_job_expertise_skills_labels":241,"max_cpc":84,"actual_cpc":84},51984,"first-vp-regional-data-analytics-group-compliance-united-overseas-bank-ltd","First VP, Regional Data Analytics, Group Compliance",{"name":29,"slug":30,"logo_url":4},[32],[34],[41],{"r":44,"sql":44,"hive":44,"spark":44,"hadoop":44,"impala":44,"python":45,"data visualization tools":44},[47,48,49,50,97,98,184,239],"Data visualization tools",{"data science":45,"schema design":44,"data analytics":45,"machine learning":45,"model governance":45,"model validation":45,"aml\u002Fafc compliance":44,"big data analytics":45,"regulatory knowledge":44,"statistical modeling":45,"dimensional data modeling":44},[242,243,244,245,246,247,248,249,250,251,252],"Data analytics","Data science","Machine learning","Statistical modeling","Model validation","Model governance","Big data analytics","Schema design","Dimensional data modeling","AML\u002FAFC compliance","Regulatory knowledge",{"industry":254,"employment_type":261,"expertise_skills":264,"it_skills":317,"salary_currency":374,"processed_working_hours":376},[255,258],{"key":256,"label":257,"count":21},"banking","Banking",{"key":259,"label":260,"count":182},"financial services","Financial Services",[262],{"key":42,"label":263,"count":21},"PERMANENT",[265,267,270,274,276,278,280,282,284,286,288,290,292,294,296,298,300,302,304,306,308,310,312,314],{"key":266,"label":64,"slug":266,"count":21},"model-governance",{"key":268,"label":62,"slug":268,"count":269},"machine-learning",6,{"key":271,"label":272,"slug":271,"count":273},"project-management","Project management",5,{"key":275,"label":61,"slug":275,"count":45},"data-science",{"key":277,"label":82,"slug":277,"count":45},"regulatory-compliance",{"key":279,"label":71,"slug":279,"count":182},"model-testing",{"key":281,"label":70,"slug":281,"count":182},"model-training",{"key":283,"label":78,"slug":283,"count":182},"distributed-databases",{"key":285,"label":66,"slug":285,"count":182},"data-wrangling",{"key":287,"label":68,"slug":287,"count":182},"feature-selection",{"key":289,"label":200,"slug":289,"count":182},"statistical-modeling",{"key":291,"label":65,"slug":291,"count":182},"big-data-analytics",{"key":293,"label":228,"slug":293,"count":182},"model-validation",{"key":295,"label":67,"slug":295,"count":182},"exploratory-data-analysis",{"key":297,"label":59,"slug":297,"count":182},"fraud-detection",{"key":299,"label":202,"slug":299,"count":182},"risk-management",{"key":301,"label":69,"slug":301,"count":182},"model-selection",{"key":303,"label":142,"slug":303,"count":84},"data-lineage",{"key":305,"label":146,"slug":305,"count":84},"data-modeling",{"key":307,"label":141,"slug":307,"count":84},"data-quality",{"key":309,"label":170,"slug":309,"count":84},"data-science-integration",{"key":311,"label":107,"slug":311,"count":84},"data-visualization",{"key":313,"label":198,"slug":313,"count":84},"deep-learning",{"key":315,"label":316,"slug":315,"count":84},"dimensional-data-modeling","Dimensional Data Modeling",[318,320,322,324,326,328,330,333,335,338,340,342,344,346,348,350,352,355,358,361,364,366,368,371],{"key":319,"label":47,"slug":319,"count":269},"python",{"key":321,"label":97,"slug":321,"count":273},"sql",{"key":323,"label":49,"slug":323,"count":45},"spark",{"key":325,"label":48,"slug":325,"count":45},"hive",{"key":327,"label":51,"slug":327,"count":44},"pandas",{"key":329,"label":184,"slug":329,"count":44},"hadoop",{"key":331,"label":332,"slug":331,"count":44},"tensorflow","Tensorflow",{"key":334,"label":223,"slug":334,"count":44},"scikit-learn",{"key":336,"label":337,"slug":336,"count":182},"ms-powerbi","MS PowerBI",{"key":339,"label":50,"slug":339,"count":182},"impala",{"key":341,"label":98,"slug":341,"count":182},"r",{"key":343,"label":190,"slug":343,"count":182},"jenkins",{"key":345,"label":191,"slug":345,"count":182},"jira",{"key":347,"label":52,"slug":347,"count":182},"keras",{"key":349,"label":189,"slug":349,"count":182},"git",{"key":351,"label":185,"slug":351,"count":182},"trino",{"key":353,"label":354,"slug":353,"count":84},"ms-access","MS Access",{"key":356,"label":357,"slug":356,"count":84},"ms-excel","MS Excel",{"key":359,"label":360,"slug":359,"count":84},"ms-powerpoint","MS PowerPoint",{"key":362,"label":363,"slug":362,"count":84},"ms-word","MS Word",{"key":365,"label":55,"slug":365,"count":84},"natural-language-processing",{"key":367,"label":56,"slug":367,"count":84},"network-link-analysis",{"key":369,"label":370,"slug":369,"count":84},"numpy","Numpy",{"key":372,"label":373,"slug":372,"count":84},"pytorch","Pytorch",[375],{"key":38,"label":38,"count":21},[377],{"key":41,"label":41,"count":21},{"total":379,"jobs":380},0,[]]