Quantitative Risk Analytics Strategist

Quantitative Risk Analytics Strategist at Morgan Stanley

Morgan Stanley is a leading global financial services firm that has been a driving force in the industry for 90 years. With a strong reputation for innovation, integrity, and teamwork, we are committed to delivering exceptional results to our clients and shareholders. Our people are our greatest asset, and we are dedicated to fostering a culture of collaboration, creativity, and excellence.

Role Overview

This role focuses on supporting Trading Risk Management by delivering accurate and timely data. Responsibilities include designing, implementing, and maintaining reporting solutions, ensuring high data quality and enabling fast access to key metrics. The role also involves aggregating data from multiple sources, validating, and creating tools to distribute insights across the organization. Additionally, it contributes to the continuous improvement of data processes and supports the development of scalable, efficient reporting workflows. The role plays a key part in ensuring stakeholders can make informed decisions based on reliable and well-structured information.

Key Responsibilities

• Write, test, and maintain KDB+/Q code for data ingestion, transformation, and querying.
• Design checks, validation rules, and monitoring tools that ensure accuracy across historical and intraday datasets.
• Build components that power internal reports and analytics dashboards, with a focus on consistency and reliability.
• Optimize queries, schemas, and processes to improve retrieval speed and system performance.
• Work with data analysts, risk managers, and other engineers to understand reporting needs and translate them into robust workflows.
• Contribute to daily operations, troubleshoot issues, and support ongoing improvements to the data systems.

Requirements

• Degree in Computer Science, Math, Engineering, Physics, or another quantitative field.
• Strong knowledge of Python, C++, or Java; familiarity with KDB+/Q is a plus but can be developed on the job.
• Solid problem solving & math foundations.
• Able to investigate data issues, reason about system behavior, and propose technical solutions.
• High resilience to work at the forefront of business decision-making.
• Clear communication in English and the ability to collaborate with colleagues who rely on accurate and timely reporting.
• Minimum 3 years of professional experience in a data-focused or backend engineering role.

What You Can Expect From Morgan Stanley

At Morgan Stanley, we raise, manage, and allocate capital for our clients – helping them reach their goals. We do it in a way that’s differentiated – and we’ve done that for 90 years. Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - aren’t just beliefs, they guide the decisions we make every day to do what's best for our clients, communities, and more than 80,000 employees in 1,200 offices across 42 countries. At Morgan Stanley, you’ll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There’s also ample opportunity to move about the business for those who show passion and grit in their work.

Key skills/competency

• Data Analytics
• Risk Management
• KDB+/Q Development
• Python/C++/Java
• Data Quality
• Reporting Solutions
• System Performance Optimization
• Financial Services
• Problem Solving
• Backend Engineering