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JobsMorgan Stanley

Data Scientist / GenAI Developer - eTrading (eRates)

Morgan Stanley

Data Scientist / GenAI Developer - eTrading (eRates)

Morgan Stanley

Budapest, Hungary

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Remote work flexibility

Wellness benefits

Top Tier compensation with equity

Health, dental, and vision coverage

Flexible PTO policy

Learning and development stipend

Required Skills

TensorFlow

Python

Airflow

We're seeking a new colleague to join our Budapest team as a Data Scientist / GenAI Developer in Budapest.
In the Fixed Income division, we work in fast-paced and constantly changing global markets to assess and manage risk, trade securities, manage relationships with clients, and structure and execute innovative transactions.
The e Rates (electronic rates) Strategists in Budapest are a data-driven team supporting algorithmic European Government Bond (EGB) trading and building GenAI solutions for the business. Alongside risk handling, trading signal development, and performance monitoring, the team's GenAI specialists develop tools that support Sales and Trading, maintain AI-driven automation, and design data pipelines to solve ad hoc business problems.
As we expand our GenAI capabilities, the team is focused on creating scalable AI services, improving model quality and reliability, and integrating modern AI tooling into front-office and operational workflows.

You will:

  • Develop GenAI tools and solutions to support Sales, Trading, and internal workflows.
  • Build and maintain data pipelines and services for AI applications.
  • Monitor and enhance AI-driven automations for quality and performance.
  • Partner with global teams and front-office stakeholders to translate business needs into technical solutions.

You have:

  • Degree in a quantitative field such as Computer Science, Mathematics, Statistics, Physics, or related discipline.
  • Solid problem solving and mathematical foundations, and an interest in the financial industry.
  • Strong communication skills (ability to present complex ideas clearly).
  • Strong Python skills and experience building applications and backend services.
  • Experience with data analysis and databases (SQL / time-series).
  • Familiarity with LLM / GenAI patterns (RAG, tool use, AI-assisted coding).
  • Analytical mindset, high attention to detail, and ability to handle multiple projects.

Nice to have:

  • Experience tuning prompts and interactions to improve LLM behaviour and UX.
  • Hands-on GenAI work with Lang Chain, Lang Graph or similar frameworks.
  • Understanding of neural networks and modern NLP / LLM concepts.
  • Experience designing tests and evaluations for GenAI systems.
  • Experience taking projects from prototype to production.
  • Experience with RAG, structured generation (JSON / SQL / function calling), and agent / tool-calling setups.
  • Experience working in an agile team.

# # #BPMMWHAT 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