Senior Quantitative Analyst

About MultiBank Group

Role Overview

Key Responsibilities

• Design, build, validate, and maintain quantitative models and machine-learning methods using financial, trading, client, and market data.
• Translate trading and business questions into clear research hypotheses, measurable outcomes, and practical analytical solutions.
• Use Python, PySpark, and SQL to extract, transform, validate, and analyse large datasets from multiple trading and business systems.
• Engineer, document, and validate robust features from transactional, market, and operational data.
• Apply appropriate statistical, machine-learning, and AI techniques to identify meaningful patterns and generate actionable insights.
• Evaluate model performance, robustness, stability, and explainability, communicating limitations and recommendations clearly.
• Develop scalable data and model workflows using AWS-based data infrastructure, including Glue, SageMaker, Athena, and related services.
• Contribute to the ongoing development and improvement of analytical tooling, data pipelines, and model workflows.
• Collaborate with Data Analysts and other stakeholders to maintain reliable data foundations and support complex analytical work.
• Support critical desk projects, including client profiling and market regime identification.

Qualifications and Requirements

• 5-8+ years of professional experience in quantitative analysis, data science, machine learning, quantitative research, or a similar analytical role.
• Strong Python experience for data analysis, modelling, feature engineering, automation, and production-quality analytical workflows.
• Strong SQL skills and experience working with large, complex datasets.
• Experience with PySpark or other distributed data-processing frameworks.
• Demonstrated experience building and evaluating predictive models, including supervised and unsupervised machine-learning methods.
• Strong understanding of statistical modelling, time-series analysis, model validation, and the practical trade-offs involved in deploying models.
• Experience working with financial markets, trading, brokerage, or other high-frequency transactional datasets; FX, CFD, or brokerage experience is strongly preferred.
• Experience applying LLMs in data or analytics workflows, including an understanding of evaluation, limitations, and appropriate controls.
• Ability to investigate and reconstruct complex sequences of business, trading, and system events and translate them into reliable analytical logic.
• Strong communication and problem-solving skills, with the ability to explain technical findings, assumptions, and risks clearly.

Preferred Profile

• Experience with MetaQuotes MT4 and MT5 databases and trading data structures.
• Experience with AWS data and analytics services, including Glue, Data Catalog, Athena, and SageMaker.
• Experience applying machine-learning methods to client, trading, market, or other financial datasets.
• Familiarity with model monitoring, reproducible research, version control, testing, and model documentation.
• Understanding of dealing operations, liquidity management, risk management, hedging, P&L reporting, or related brokerage workflows.
• Experience designing analytical products, decision-support workflows, or internal tools used by business stakeholders.
• A genuine interest in financial markets and trading, evidenced through personal study, research, or practical engagement.
• A degree in mathematics, statistics, computer science, engineering, physics, econometrics, financial engineering, or another quantitative discipline.

Why Join Us

• Work with an industry-leading global financial institution.
• Competitive salary and comprehensive employee benefits.
• Opportunities for professional growth and career advancement.
• Collaborative, inclusive, and dynamic work environment.
• Commitment to innovation, client engagement excellence, and performance-driven success.