Financial & Data Analyst

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Fort Technologies Inc., is seeking the following. Apply via Dice today!Position Description: We are seeking a highly skilled Data & Financial Engineer to design, implement, and optimize financial models, analytics tools, and quantitative solutions. The ideal candidate will bridge the gap between finance and technology, leveraging mathematical modelling, data engineering, and programming expertise to solve complex financial problems. This role involves close collaboration with portfolio managers, risk teams, and software engineers to develop models that drive trading strategies, risk measurement, and financial decision-making.Responsibilities:Design, implement and test quantitative models for quantitative analytics and risk.Validate input and outputs for analytics models against historical and computed data to 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.Compute and analyze singe security risk metrics (duration, convexity, spreads, krds, krcs) for any deviations or enhancementsSupport fixed income analytics and structured product modelling incorporating cash flows from vendors.Work with traders, portfolio managers, and risk officers to interpret results and refine models.Liaise with software development teams to integrate models into production systems.Finance Knowledge:Understanding of fixed income analytics, portfolio theory, and risk management.Experience with Bloomberg, Refinitiv, FactSet, or similar market data tools.Experience working with vendor platforms like Yield book, Intex, Aladdin, etcTechnical Skills:Strong proficiency in Python for quantitative modelling.Experience with numerical methods, optimization, and Monte Carlo simulations.Knowledge of databases (SQL, NoSQL) and cloud platforms (AWS, Azure, Google Cloud Platform).Familiarity with financial libraries (QuantLib, Pandas, NumPy, SciPy).