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Quantitative Risk Analytics Strategist

Morgan Stanley

Quantitative Risk Analytics Strategist

Morgan Stanley

Budapest, Hungary

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Competitive salary and equity package

Comprehensive health, dental, and vision insurance

Generous paid time off and holidays

401(k) matching

Professional development budget

Equity

Healthcare

Learning

Required Skills

Python

JavaScript

Node.js

Join a Global Leader in Financial Services: 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 key part in ensuring the 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 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 behaviour, 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

# BPMM

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.
To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices into your browser.

Certified Persons Regulatory Requirements:

If t his role is deemed a Certified role and may require the role holder to hold mandatory regulatory qualifications or the minimum qualifications to meet internal company benchmarks.

Flexible work statement

Interested in flexible working opportunities? Morgan Stanley empowers employees to have greater freedom of choice through flexible working arrangements. Speak to our recruitment team to find out more.
Morgan Stanley is an equal opportunities employer. We work to provide a supportive and inclusive environment where all individuals can maximize their full potential. Our skilled and creative workforce is comprised of individuals drawn from a broad cross section of the global communities in which we operate and who reflect a variety of backgrounds, talents, perspectives, and experiences. Our strong commitment to a culture of inclusion is evident through our constant focus on recruiting, developing, and advancing individuals based on their skills and talents.

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About Morgan Stanley

Morgan Stanley

A financial services company that offers securities, asset management, and credit services.

10,001+

Employees

New York

Headquarters

Reviews

3.5

4 reviews

Work Life Balance

3.0

Compensation

2.5

Culture

3.2

Career

3.0

Management

3.0

35%

Recommend to a Friend

Pros

Skills evaluation through business plans and projects

Direct access to senior leadership interviews

Conversational interview format

Cons

Automated resume screening system issues

Focus on formatting over qualifications

Compensation concerns and salary expectations

Salary Ranges

11,766 data points

Junior/L3

Mid/L4

Senior/L5

Junior/L3 · Analyst

1,682 reports

$114,371

total / year

Base

$96,366

Stock

-

Bonus

$18,005

$77,808

$170,800

Interview Experience

6 interviews

Difficulty

3.0

/ 5

Duration

21-35 weeks

Experience

Positive 16%

Neutral 84%

Negative 0%

Interview Process

1

Initial screening (HR/HireVue)

2

Technical rounds

3

Manager/Senior leadership interviews

4

Final round/Superday

Common Questions

Technical knowledge assessment

Behavioral questions

Role-specific scenarios

Leadership and teamwork examples