Financial Engineer – Quantitative Analytics & Risk (Python and Sql)

Financial Engineer – Quantitative Analytics & RiskYou can share your cv at info@unloadbox.comRole OverviewWe are seeking a Financial Engineer to work at the intersection of Quantitative Analytics,Risk Management and Technology. The role will involve working closely with Quant teams,Risk Managers, Portfolio Managers and Technology teams to build solutions, wrappers,services and integrations around quantitative models and analytics.The ideal candidate combines strong financial markets and risk knowledge with hands-onprogramming and analytical skills, and is comfortable explaining quantitative results andinvestigating differences in risk and attribution numbers.Key Responsibilities Work with Quant, Risk and Investment teams to understand quantitative models,analytics and business requirements.  Support Fixed Income and structured-product analytics, including pricing, risk andcash-flow analytics.  Build wrappers, services, APIs and integrations around quantitative/risk models andanalytical platforms.  Analyze and explain changes or differences in risk, performance and attributionresults.  Validate input and outputs for analytics models against historical and computed datato ensure accuracy and robustness.  Acquire, clean, and analyze large-scale financial datasets from multiple sources.  Build data pipelines for real-time and batch processing of market and reference data Investigate breaks across positions, market data, reference data, cash flows, modelinputs and analytics.  Develop functional and statistical data/analytics validation checks and support root-cause analysis.  Collaborate with engineering teams to productionize quantitative solutions and datapipelines.Required Skills & Experience 5+ years in Financial Engineering, Quantitative Analytics, Risk Analytics, FES,Quant Development or Investment Analytics.  Strong experience working directly with Quant teams, Risk Managers and/or PortfolioManagers.  Strong Python and SQL skills; experience building production-quality analyticalsolutions.  Strong understanding of Fixed Income and risk analytics Ability to understand why risk or attribution numbers change and explain the driversto business stakeholders. Understanding of the trade lifecycle through risk and attribution.Strongly Preferred Hands-on experience with Mortgage / MBS, ABS, Credit or other structured products.  Experience with mortgage/ABS cash flows, prepayment, default and embeddedoptionality.  Experience working in an FES / Quantitative Analytics environment supportinginstitutional investment or risk teams.  Knowledge of QuantLib, NumPy, Pandas, SciPy, APIs and financial data pipelines.