Global Market Risk & Data Science (Hadoop) Analyst

Job title: Global Market Risk & Data Science (Hadoop) Analyst
Contract type: Permanent
Location: Selangor
Salary: RM Attractive per month
Reference: A003959 (ATFB-004383)
Contact name: Afif Kamal
Contact email:
Published: 9 days ago

Job description

​About our client

A leading global professional services company since 1979 serving more than 250 clients in 19 industries across Southeast Asia, including many of the largest companies and organisations in the region. They provides a diverse range of innovative solutions in consulting, strategy, digital, technology, and operations. With a commitment to driving business transformation and delivering measurable outcomes, this company leverages on cutting-edge technology and industry expertise to empower clients across various sectors. Through collaborative partnerships and a strong focus on sustainability, inclusion, and corporate citizenship, this company contributes to shaping a more resilient and responsible future for businesses and communities alike.

About the role

We are seeking a talented and experienced Global Market Risk & Data Science Analyst with expertise in Hadoop technology and Murex Value at Risk (VaR) to join our team. As a key member of our Global Market Risk team, you will play a crucial role in analyzing market risk data, implementing data science techniques, and leveraging Hadoop technology to enhance risk management strategies for our clients in the financial sector.

Your responsibilities

  • Utilize advanced data science techniques and analytics to analyze market risk data and identify trends, patterns, and anomalies.

  • Develop and implement risk models, algorithms, and methodologies to measure and manage market risk exposure effectively.

  • Collaborate with cross-functional teams to gather, process, and analyze large volumes of market data using Hadoop ecosystem tools and technologies.

  • Design, develop, and maintain data pipelines, data processing workflows, and data visualization dashboards to support market risk analytics and reporting.

  • Enhance existing risk management frameworks and methodologies, incorporating Murex Value at Risk (VaR) principles and best practices.

  • Conduct scenario analysis, stress testing, and back-testing of risk models to evaluate their accuracy, robustness, and performance.

  • Communicate findings, insights, and recommendations to stakeholders, including risk managers, traders, and senior executives, in a clear and concise manner.

  • Stay updated on industry trends, regulatory requirements, and emerging technologies related to global market risk management and data science.

You will have

  • Bachelor's or Master's degree in Finance, Economics, Mathematics, Statistics, Computer Science, or related field.

  • 2-5 years of experience in global market risk management, data science, and analytics in the financial services industry.

  • Proficiency in Hadoop ecosystem tools and technologies (HDFS, MapReduce, Hive, Spark, etc.).

  • Hands-on experience with Murex Value at Risk (VaR) calculations and risk modeling.

  • Strong quantitative and analytical skills, with a solid understanding of financial markets, trading products, and risk management concepts.

  • Experience in programming languages such as Python, R, or Java for data analysis and modeling.

  • Knowledge of machine learning algorithms, statistical techniques, and data visualization tools.

  • Excellent communication skills, with the ability to present complex concepts and findings to both technical and non-technical audiences.

  • Ability to work independently and collaboratively in a fast-paced and dynamic environment.

  • Relevant certifications in risk management, data science, or related fields (e.g., FRM, CFA, CQF, CRISP-DM) are a plus.

If you are seeking to join a collaborative team and are prepared to assume significant team responsibilities, this opportunity is tailored for you.

Interested candidates, APPLY today or email your comprehensive resume/CV to

Kindly note that only successful or shortlisted candidates will be contacted via WhatsApp, phone call, or email.

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