[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"job-search-\u002Fde-us\u002Fjobs-by-expertise\u002Ffinancial-engineering":3,"seo-content-expertise-financial-engineering-us":103,"expertise-filters-\u002Fde-us\u002Fjobs-by-expertise\u002Ffinancial-engineering":132,"featured-jobs-\u002Fde-us\u002Fjobs-by-expertise\u002Ffinancial-engineering":232},{"total":4,"jobs":5},3,[6,54,83],{"id":7,"slug":8,"title":9,"raw_title":10,"is_featured":11,"company":12,"raw_hiringOrganization_logo_url":10,"processed_city_gmaps":15,"processed_country_iso_code_gmaps":17,"processed_home_office":19,"processed_salary_min":20,"processed_salary_max":21,"processed_salary_currency":22,"processed_salary_source":23,"processed_working_hours":24,"processed_employment_types":26,"processed_it_skills":27,"processed_it_skills_labels":30,"processed_job_expertise_skills":39,"processed_job_expertise_skills_labels":40,"max_cpc":52,"actual_cpc":53},84410,"quantitative-analyst-portfolio-engineering-analytics-invesco-advisors-inc","Quantitative Analyst, Portfolio Engineering & Analytics",null,false,{"name":13,"slug":14,"logo_url":10},"Invesco Advisors Inc.","invesco-advisors-inc",[16],"Boston",[18],"US","hybrid",130000,135000,"USD","estimated",[25],"FULL_TIME","permanent",{"sql":4,"python":28,"pytorch":4,"tensorflow":4,"scikit-learn":4,"generative ai":29,"api development":4,"high performance computing":4},4,2,[31,32,33,34,35,36,37,38],"Python","SQL","scikit-learn","TensorFlow","PyTorch","Generative AI","API development","High Performance Computing",{"statistics":28,"cfa progress":29,"optimization":28,"data management":4,"neural networks":4,"asset allocation":28,"machine learning":4,"financial engineering":28,"quantitative research":28,"portfolio construction":28,"risk models (barraone, axioma)":29},[41,42,43,44,45,46,47,48,49,50,51],"Financial Engineering","Statistics","Optimization","Portfolio Construction","Asset Allocation","Machine Learning","Neural Networks","Risk Models (BarraOne, Axioma)","CFA Progress","Data Management","Quantitative Research",1,1.5,{"id":55,"slug":56,"title":57,"raw_title":10,"is_featured":11,"company":58,"raw_hiringOrganization_logo_url":10,"processed_city_gmaps":61,"processed_country_iso_code_gmaps":63,"processed_home_office":64,"processed_salary_min":65,"processed_salary_max":66,"processed_salary_currency":22,"processed_salary_source":23,"processed_working_hours":67,"processed_employment_types":26,"processed_it_skills":68,"processed_it_skills_labels":69,"processed_job_expertise_skills":75,"processed_job_expertise_skills_labels":76,"max_cpc":52,"actual_cpc":53},85670,"research-associatevp-alphawise-quant-researcher-new-york-morgan-stanley-europe-se","Research - Associate\u002FVP, AlphaWise Quant Researcher (New York)",{"name":59,"slug":60,"logo_url":10},"Morgan Stanley Europe SE","morgan-stanley-europe-se",[62],"New York",[18],"onsite",120000,250000,[25],{"llms":4,"q\u002Fkdb":28,"python":28,"databases":4,"unix\u002Flinux":28,"deep learning":4},[31,70,71,72,73,74],"Q\u002Fkdb","UNIX\u002FLinux","Deep Learning","LLMs","Databases",{"backtesting":28,"equity research":4,"financial engineering":4,"quantitative modeling":28,"quantitative research":28,"large dataset analysis":28,"alternative data analysis":4,"statistical learning methods":28},[51,77,78,79,80,81,82,41],"Statistical Learning Methods","Large Dataset Analysis","Backtesting","Quantitative Modeling","Equity Research","Alternative Data Analysis",{"id":84,"slug":85,"title":86,"raw_title":10,"is_featured":11,"company":87,"raw_hiringOrganization_logo_url":10,"processed_city_gmaps":90,"processed_country_iso_code_gmaps":91,"processed_home_office":64,"processed_salary_min":92,"processed_salary_max":93,"processed_salary_currency":22,"processed_salary_source":23,"processed_working_hours":94,"processed_employment_types":26,"processed_it_skills":95,"processed_it_skills_labels":96,"processed_job_expertise_skills":97,"processed_job_expertise_skills_labels":98,"max_cpc":52,"actual_cpc":53},60094,"senior-market-analyst-derivatives-usa016-refinitiv-us-llc","Senior Market Analyst, Derivatives",{"name":88,"slug":89,"logo_url":10},"Refinitiv US LLC","refinitiv-us-llc",[62],[18],113300,188800,[25],{"python":28},[31],{"valuation":28,"risk management":4,"derivatives pricing":28,"financial engineering":28,"quantitative analytics":28},[99,100,101,41,102],"Derivatives Pricing","Quantitative Analytics","Valuation","Risk Management",{"image_path":104,"content_de":105,"content_en":118,"composite_key":131,"last_updated":10},"\u002Fimages\u002Fexpertise\u002Ffinancial-engineering.webp",{"tab1":106,"tab2":109,"tab3":112,"tab4":115},{"title":107,"content":108},"Bedeutung & Relevanz","Financial Engineering spielt eine entscheidende Rolle in den [Vereinigten Staaten](\u002Fsearch), wo es als strategisches Werkzeug zur Entwicklung innovativer Finanzprodukte und Risikomanagementlösungen dient. In einem Markt, der von komplexen Finanzinstrumenten und volatilen Märkten geprägt ist, ermöglicht Financial Engineering die Modellierung und Optimierung von Anlagestrategien, was insbesondere für Unternehmen wie [Pacific Investment Mgt Co. LLC](\u002Fcompany\u002Fpacific-investment-mgt-co-llc) in [Newport Beach](\u002Fjobs-in-newport-beach) von großer Bedeutung ist. Durch den Einsatz quantitativer Methoden trägt es zur Steigerung der Renditen und zur Absicherung gegen Marktrisiken bei, was in der [Investment Management](\u002Fjobs-by-industry\u002Finvestment-management)- und [Finance](\u002Fjobs-by-industry\u002Ffinance)-Branche unverzichtbar ist. In den USA, wo regulatorische Anforderungen und Wettbewerbsdruck hoch sind, hilft Financial Engineering dabei, Compliance zu gewährleisten und Wettbewerbsvorteile zu sichern, indem es datengestützte Entscheidungen fördert und die Effizienz in Prozessen wie [Portfolio Management](\u002Fjobs-by-expertise\u002Fportfolio-management) und [Risk Management](\u002Fjobs-by-expertise\u002Frisk-management) verbessert.",{"title":110,"content":111},"Top-Branchen & Standorte","In den [Vereinigten Staaten](\u002Fsearch) ist Financial Engineering besonders in Branchen wie [Investment Management](\u002Fjobs-by-industry\u002Finvestment-management) und [Finance](\u002Fjobs-by-industry\u002Ffinance) gefragt, wo es zur Entwicklung von Anlagestrategien und Risikomodellen eingesetzt wird. Top-Standorte wie [Newport Beach](\u002Fjobs-in-newport-beach) sind Hotspots für diese Expertise, da sie Heimat führender Unternehmen im [Asset Management](\u002Fjobs-by-industry\u002Fasset-management) sind. Weitere bedeutende Industrien umfassen [Banking](\u002Fjobs-by-industry\u002Fbanking) und [Asset Management Financial Services](\u002Fjobs-by-industry\u002Fasset-management-financial-services), in denen Financial Engineering zur Optimierung von Finanzprodukten und zur Verbesserung der [Process Improvement](\u002Fjobs-by-expertise\u002Fprocess-improvement) beiträgt. In Städten mit starkem Finanzsektor unterstützt diese Fähigkeit die lokale Wirtschaft, indem sie Arbeitsplätze schafft und Innovationen in Bereichen wie [Financial Markets](\u002Fjobs-by-expertise\u002Ffinancial-markets) vorantreibt. Die Nachfrage konzentriert sich oft auf Regionen mit hoher Finanzaktivität, wo Expertise in [Quantitative Research](\u002Fjobs-by-expertise\u002Fquantitative-research) und [Risk Assessment](\u002Fjobs-by-expertise\u002Frisk-assessment) geschätzt wird.",{"title":113,"content":114},"Gefragte Skills & Arbeitgeber","Führende Unternehmen in den [Vereinigten Staaten](\u002Fsearch), darunter [Pacific Investment Mgt Co. LLC](\u002Fcompany\u002Fpacific-investment-mgt-co-llc), suchen nach Profilen mit Financial Engineering-Kenntnissen, kombiniert mit Expertise in [Quantitative Research](\u002Fjobs-by-expertise\u002Fquantitative-research), [Risk Management](\u002Fjobs-by-expertise\u002Frisk-management) und [Process Enhancement](\u002Fjobs-by-expertise\u002Fprocess-improvement). Weitere gefragte Bereiche sind [Collateral Management](\u002Fjobs-by-expertise\u002Fcollateral-management), [Statistics](\u002Fjobs-by-expertise\u002Fstatistics), [Probability](\u002Fjobs-by-expertise\u002Fprobability) und [Data Science](\u002Fjobs-by-expertise\u002Fdata-science), die zur Entwicklung robuster Finanzmodelle beitragen. [Machine Learning](\u002Fjobs-by-expertise\u002Fmachine-learning) und [Financial Products](\u002Fjobs-by-expertise\u002Ffinancial-products) sind ebenfalls Schlüssel, um systematische Handelsstrategien und [Investment Strategy](\u002Fjobs-by-expertise\u002Finvestment-strategy) zu optimieren. Arbeitgeber schätzen Fähigkeiten in [Pattern Recognition](\u002Fjobs-by-expertise\u002Fpattern-recognition), [Fixed Income Markets](\u002Fjobs-by-expertise\u002Ffixed-income-markets) und [Optimization Methods](\u002Fjobs-by-expertise\u002Foptimization-methods), die in [Portfolio Construction](\u002Fjobs-by-expertise\u002Fportfolio-construction) und [Alpha Signal Development](\u002Fjobs-by-expertise\u002Falpha-signal-development) eingesetzt werden. Zudem sind Kenntnisse in [Natural Language Processing](\u002Fjobs-by-expertise\u002Fnatural-language-processing), [Econometrics](\u002Fjobs-by-expertise\u002Feconometrics) und [Asset Pricing](\u002Fjobs-by-expertise\u002Fasset-pricing) entscheidend, um in wettbewerbsintensiven Märkten wie den USA zu bestehen.",{"title":116,"content":117},"Karriere & Entwicklung","Karrierewege im Financial Engineering in den [Vereinigten Staaten](\u002Fsearch) umfassen Rollen wie Quantitative Analyst, Risk Manager oder Portfolio Manager, die oft Expertise in [Quantitative Research](\u002Fjobs-by-expertise\u002Fquantitative-research), [Risk Analysis](\u002Fjobs-by-expertise\u002Frisk-analysis) und [Finance Theory](\u002Fjobs-by-expertise\u002Ffinance-theory) erfordern. Um diese Fähigkeiten zu erlernen, sind fortgeschrittene Studien in Finanzmathematik oder Data Science empfehlenswert, ergänzt durch praktische Erfahrung mit IT-Skills wie [Python](\u002Fjobs-by-skill\u002Fpython), [SQL](\u002Fjobs-by-skill\u002Fsql) und [VBA](\u002Fjobs-by-skill\u002Fvba). Weitere relevante Technologien sind [C#](\u002Fjobs-by-skill\u002Fc), [C++](\u002Fjobs-by-skill\u002Fc), [Java](\u002Fjobs-by-skill\u002Fjava) und [Modern Databases](\u002Fjobs-by-skill\u002Fmodern-databases), die in [Relational Databases](\u002Fjobs-by-skill\u002Frelational-databases) und [Object-Oriented Programming](\u002Fjobs-by-skill\u002Fobject-oriented-programming) Anwendung finden. Tools wie [MATLAB](\u002Fjobs-by-skill\u002Fmatlab) und Kenntnisse in [Programming](\u002Fjobs-by-skill\u002Fprogramming), [Data Science](\u002Fjobs-by-skill\u002Fdata-science) und [Machine Learning](\u002Fjobs-by-skill\u002Fmachine-learning) unterstützen die Entwicklung in Bereichen wie [Asset Allocation](\u002Fjobs-by-expertise\u002Fasset-allocation), [Client Analytics](\u002Fjobs-by-expertise\u002Fclient-analytics) und [Portfolio Theory](\u002Fjobs-by-expertise\u002Fportfolio-theory). Fortbildungen in [Time Series Analysis](\u002Fjobs-by-expertise\u002Ftime-series-analysis) und [Portfolio Optimization](\u002Fjobs-by-expertise\u002Fportfolio-optimization) können die Karrierechancen in dynamischen US-Märkten weiter steigern.",{"tab1":119,"tab2":122,"tab3":125,"tab4":128},{"title":120,"content":121},"Strategic Importance","Financial Engineering holds immense strategic importance in the [Vereinigten Staaten](\u002Fsearch) financial landscape, serving as the backbone of modern investment management and risk mitigation strategies. This interdisciplinary field combines mathematical modeling, computational techniques, and financial theory to create sophisticated instruments and strategies that drive market efficiency and innovation. In the competitive [Vereinigten Staaten](\u002Fsearch) market, financial engineers develop complex derivatives, structured products, and algorithmic trading systems that enable institutions to manage risk, enhance returns, and create value for clients.\n\nThe relevance of Financial Engineering has surged with the increasing complexity of global financial markets and the rapid adoption of technology in finance. Companies leverage these skills to develop quantitative models for pricing exotic options, optimizing portfolio construction, and implementing systematic trading strategies. The field's importance extends beyond traditional banking to encompass hedge funds, asset management firms, and fintech companies seeking competitive advantages through advanced analytical capabilities and innovative financial product development.",{"title":123,"content":124},"Top Industries & Locations","Financial Engineering professionals find strong demand across multiple industries in the [Vereinigten Staaten](\u002Fsearch), with [investment management](\u002Fjobs-by-industry\u002Fasset-management) and [finance](\u002Fjobs-by-industry\u002Fbanking) leading the way. The [investment management](\u002Fjobs-by-industry\u002Fasset-management) sector particularly values these skills for developing sophisticated portfolio strategies and risk management frameworks. Major financial hubs like [Newport Beach](\u002Fjobs-in-newport-beach) serve as epicenters for financial engineering talent, hosting prominent firms that drive innovation in quantitative finance and algorithmic trading.\n\nBeyond traditional finance, the expertise extends to insurance companies developing complex risk models, consulting firms providing quantitative advisory services, and technology companies building financial platforms. The concentration of opportunities in key financial centers reflects the collaborative ecosystem required for cutting-edge financial innovation, where proximity to research institutions, talent pools, and capital markets creates optimal conditions for financial engineering excellence.",{"title":126,"content":127},"In-Demand Skills & Employers","Leading companies in the [Vereinigten Staaten](\u002Fsearch) actively seek Financial Engineering professionals with specialized expertise. [Pacific Investment Mgt Co. LLC](\u002Fcompany\u002Fpacific-investment-mgt-co-llc) exemplifies the type of employer that heavily relies on financial engineering talent for developing sophisticated investment strategies and risk management frameworks. These organizations require deep expertise in [quantitative research](\u002Fjobs-by-expertise\u002Ffinancial-analysis), [risk management](\u002Fjobs-by-expertise\u002Frisk-management), and [financial modeling](\u002Fjobs-by-expertise\u002Ffinancial-modeling) to navigate complex market conditions.\n\nCritical expertise areas include [portfolio management](\u002Fjobs-by-expertise\u002Fportfolio-management), systematic trading strategies, [financial markets](\u002Fjobs-by-expertise\u002Ffinancial-markets) analysis, and advanced statistical modeling. Professionals must demonstrate proficiency in developing alpha signals, optimizing portfolio construction, and implementing sophisticated risk assessment methodologies. The integration of [process improvement](\u002Fjobs-by-expertise\u002Fprocess-improvement) techniques with financial innovation creates competitive advantages for employers seeking to enhance operational efficiency while maintaining robust risk controls.",{"title":129,"content":130},"Career & Development","Financial Engineering careers in the [Vereinigten Staaten](\u002Fsearch) offer diverse pathways spanning quantitative analysis, risk management, product development, and algorithmic trading. Entry-level positions typically require strong foundations in mathematics, statistics, and programming, with progression leading to roles such as quantitative analyst, risk manager, or structured products specialist. Continuous learning is essential, with professionals needing to master both theoretical concepts like [asset pricing](\u002Fjobs-by-expertise\u002Ffinancial-analysis) and practical skills including [Python](\u002Fjobs-by-skill\u002Fpython), [SQL](\u002Fjobs-by-skill\u002Fsql), and [VBA](\u002Fjobs-by-skill\u002Fvba).\n\nDevelopment paths often involve advanced degrees in financial engineering, mathematics, or computational finance, complemented by hands-on experience with modern databases and machine learning applications. Professionals should focus on building expertise in [portfolio optimization](\u002Fjobs-by-expertise\u002Fportfolio-management), time-series analysis, and financial product development. The evolving landscape demands proficiency in [Java](\u002Fjobs-by-skill\u002Fjava), [C++](\u002Fjobs-by-skill\u002Fc), and data science tools to implement sophisticated models and trading algorithms. Career advancement typically involves specialization in areas like derivatives pricing, risk modeling, or quantitative strategy development within major financial institutions and investment firms.","expertise:financial-engineering:us",{"industry":133,"employment_type":146,"expertise_skills":149,"it_skills":194,"salary_currency":228,"processed_working_hours":230},[134,137,140,143],{"key":135,"label":136,"count":52},"financial markets infrastructure","Financial Markets Infrastructure",{"key":138,"label":139,"count":52},"data","Data",{"key":141,"label":142,"count":52},"financial services","Financial Services",{"key":144,"label":145,"count":52},"asset management","Asset Management",[147],{"key":26,"label":148,"count":4},"PERMANENT",[150,152,154,156,159,161,163,165,167,169,171,173,175,177,179,181,184,186,188,190,192],{"key":151,"label":41,"slug":151,"count":4},"financial-engineering",{"key":153,"label":51,"slug":153,"count":29},"quantitative-research",{"key":155,"label":79,"slug":155,"count":52},"backtesting",{"key":157,"label":158,"slug":157,"count":52},"cfa-progress","Cfa Progress",{"key":160,"label":50,"slug":160,"count":52},"data-management",{"key":162,"label":99,"slug":162,"count":52},"derivatives-pricing",{"key":164,"label":81,"slug":164,"count":52},"equity-research",{"key":166,"label":78,"slug":166,"count":52},"large-dataset-analysis",{"key":168,"label":46,"slug":168,"count":52},"machine-learning",{"key":170,"label":47,"slug":170,"count":52},"neural-networks",{"key":172,"label":43,"slug":172,"count":52},"optimization",{"key":174,"label":44,"slug":174,"count":52},"portfolio-construction",{"key":176,"label":100,"slug":176,"count":52},"quantitative-analytics",{"key":178,"label":80,"slug":178,"count":52},"quantitative-modeling",{"key":180,"label":102,"slug":180,"count":52},"risk-management",{"key":182,"label":183,"slug":182,"count":52},"risk-models-barraone-axioma","Risk Models (Barraone, Axioma)",{"key":185,"label":77,"slug":185,"count":52},"statistical-learning-methods",{"key":187,"label":42,"slug":187,"count":52},"statistics",{"key":189,"label":82,"slug":189,"count":52},"alternative-data-analysis",{"key":191,"label":101,"slug":191,"count":52},"valuation",{"key":193,"label":45,"slug":193,"count":52},"asset-allocation",[195,197,199,201,204,206,209,212,215,217,219,222,225],{"key":196,"label":31,"slug":196,"count":4},"python",{"key":198,"label":74,"slug":198,"count":52},"databases",{"key":200,"label":72,"slug":200,"count":52},"deep-learning",{"key":202,"label":203,"slug":202,"count":52},"generative-ai","Generative Ai",{"key":205,"label":38,"slug":205,"count":52},"high-performance-computing",{"key":207,"label":208,"slug":207,"count":52},"llms","Llms",{"key":210,"label":211,"slug":210,"count":52},"pytorch","Pytorch",{"key":213,"label":214,"slug":213,"count":52},"qkdb","Q\u002FKdb",{"key":33,"label":216,"slug":33,"count":52},"Scikit-Learn",{"key":218,"label":32,"slug":218,"count":52},"sql",{"key":220,"label":221,"slug":220,"count":52},"tensorflow","Tensorflow",{"key":223,"label":224,"slug":223,"count":52},"api-development","Api Development",{"key":226,"label":227,"slug":226,"count":52},"unixlinux","Unix\u002FLinux",[229],{"key":22,"label":22,"count":4},[231],{"key":25,"label":25,"count":4},{"total":233,"jobs":234},0,[]]