Intern - Machine Learning and Data Engineer

Overview:
**Connecting clients to markets - and talent to opportunity**

With 4,300 employees and over 400,000 retail and institutional clients from more than 80 offices spread across five continents, we’re a Fortune-100, Nasdaq-listed provider, connecting clients to the global markets - focusing on innovation, human connection, and providing world-class products and services to all types of investors.

At StoneX, we offer you the opportunity to be part of an institutional-grade financial services network that connects companies, organizations, and investors to the global markets ecosystem. As a team member, you'll benefit from our unique blend of digital platforms, comprehensive clearing and execution services, personalized high-touch support, and deep industry expertise. Elevate your career with us and make a significant impact in the world of global finance.

**Business Segment Overview**

Institutional: Immerse yourself in the best-in-class institutional-grade technology, working alongside industry experts and gaining exposure to various asset classes, such as equities, options, fixed income securities, and advanced trading, research, and management technology.

**StoneX** Internship**

Are you looking to gain real world experience in an entrepreneurial culture? Consider an internship at a thriving global financial services firm and **_launch your career with _**_StoneX_** A StoneX Internship will provide development, support, career growth, and an endless array of opportunities. You can expect to make an impact on the business and experience a career defining internship program.

**Internship Perks**:
In addition to the real-world experience, you’ll gain at StoneX, we’re excited to offer interns several perks which include the following:

- ** Compensation**: All interns are paid at a competitive rate.
- ** Socials**: Networking and acclimation to the company, office, and city are important aspects of the internship program. Socials and local favorites are planned at various points, with large events at the beginning and end of your internship.
- ** Access to Senior Leaders**: Senior leaders are involved in the internship program from day one, delivering trainings, presenting on firm business, weekly leadership calls, and even attending socials.
- ** Training**: Virtual and in-person trainings to get interns onboarded and connected with the company globally.
- ** Mentorship**: Interns have a mentor and buddy to help answer any questions and work alongside during your internship.

**Responsibilities**:
**Department Purpose**

As part of our Back office re-engineering IT project team, the individual would be required to help facilitate
- Improvement of Straight through processing (STP) by building auto-learning and auto-repair modules for payment processing
- Leverage historical data and build automated learning models that improve STP consistently as users repair transactions
- Help build alerts for outliers and exceptions through visualizations and notifications
- Adhere to organization software development guidelines including version control, unit test and automated build, test and deploy processes.

**Roles and responsibilities but not limited to:

- **
- Study and analyze business problem statements and functional specifications
- Build models by analyzing historical transaction data
- Implement and test engineering solutions
- Enable functional test and user acceptance testing

Qualifications:
**Desired Technical Skills**
- Internship experience working on Machine Learning algorithms and tools - numpy, pandas, tensorflow, pyspark
- Experience in data collection, aggregation, analysis and visualiation
- Programming languages such as Python, Java.
- Knowledge in SQL databases - MSSQL, Postgre SQL

**Early Careers Requirements**
- Pursuing a bachelor’s or masters degree from an accredited university in a relevant program and graduating in 2026 or 2027 (entering penultimate year of university)
- Available for a Jan 2026 start date for a 6-8 month program
- Must be fully authorized to work in the country the role is based

**Working environment**
- Hybrid (minimum 4 days in-office)