Quantitative Data Scientist Senior Analyst – Advanced Analytics & Algorithmic Trading for FX

Excited to grow your career? BBVA is a global company with more than 160 years of history that operates in more than 25 countries where we serve more than 80 million customers. We are more than 121,000 professionals working in multidisciplinary teams with profiles as diverse as financiers, legal experts, data scientists, developers, engineers and designers. Learn more about the area: The Quantitative & Business Solutions CoE develops and applies advanced analytics and algorithmic trading strategies to optimize trading performance, enhance data-driven decision-making, and support robust revenue generation across global markets. Fully integrated into our FX Trading, Transactional, and Sales business units, this center of excellence sits at the absolute intersection of quantitative finance, data science, and electronic trading. About the job: Role Purpose & Description: We are seeking a highly talented Data Scientist Senior Analyst to help design, build, and deploy our next-generation analytics, pricing intelligence, and algorithmic tools. In this role, you will play a pivotal part in enhancing the end-to-end value chain of our Foreign Exchange (FX) business globally. You will turn massive volumes of real-time market data into high-impact, production-ready trading and pricing models. Key Responsibilities: Transactional & Sales Analytics: Design and implement sophisticated client segmentation models, automated recommendation engines, and dynamic pricing frameworks. Collaborate closely with the FX Sales team to uncover cross-selling opportunities, mitigate churn risk, and optimize bid-ask spreads aligned with liquidity and corporate risk appetite. Algorithmic Trading & Pricing Optimization : Build, back-test, and deploy intelligent algorithms and predictive models to support automated execution and market-making strategies across FX products including Spot, Forwards, and Swaps. Conduct quantitative research on massive datasets of historical and real-time tick data. Global Collaboration & Production Engineering: Architect and deliver robust, low-latency analytical models directly into production-ready engines. Maintain continuous and proactive communication with data science and quant teams across geographies to align global execution strategies. Tech Stack Ecosystem: Run and maintain quantitative engines leveraging Python and PySpark within Amazon SageMaker, and serve actionable insights via state-of-the-art BI and data streaming platforms such as KX Insights and DOMO. What are we looking for? Requirements & Qualifications: Education : Master’s or Bachelor's degree in Physics, Mathematics, Engineering, Statistics, Computer Science, or a deeply quantitative field. Professional Experience : 2–5 years of proven experience as a Data Scientist, Quantitative Researcher, or Algorithmic Trading Developer within financial markets. Direct exposure to Capital Markets/FX structures or highly rigorous quantitative environments is required. Quantitative Skills : Strong mathematical foundations with valuable knowledge of stochastic processes, numerical methods, optimization, and machine learning architectures. Financial Knowledge : Solid understanding of financial markets and derivatives. Practical experience with FX market microstructure and electronic trading platforms (ECNs) is highly valued. Technical Proficiency : Advanced mastery of Python, PySpark, and SQL. Hands-on experience with Machine Learning libraries (TensorFlow, PyTorch, scikit-learn) and cloud infrastructure within Amazon SageMaker. Prior experience with Q/KDB+ for high-frequency time-series analytics, KX Insights, and DOMO is a strong competitive advantage. Languages : Strong command of English and Spanish. Core Soft Skills : A strong commitment to delivery and the resilience required to thrive under pressure in a fast-paced trading floor ecosystem. Skills: Advanced Analytics, Algorithmic Trading, Algorithmic Trading Strategies, Algorithms, Foreign Exchange (FX) Trading, Kdb+, Machine Learning (ML), Price Management