Machine Learning Engineer (Part time - temp)

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: With boots on the ground authenticity at the heart of everything we do, our comprehensive array of commercial products and services enable you to work directly with our clients, across hedging, risk management, execution and clearing, OTC products, commodity finance and more.

Responsibilities

Position Purpose: We are seeking a highly motivated and talented Machine Learning/Deep Learning researcher to join our growing team on a part time temporary basis. In this role, you will work closely with the trading desk and play a critical part in developing and deploying cutting-edge machine learning and deep learning models to the world of commodities trading.

Primary duties will include: 

• Research, design, and develop sophisticated machine learning and deep learning models, including but not limited to CNN, LSTM and transformers models
• Conduct thorough data analysis and feature engineering to prepare high-quality datasets for model training.
• Train, evaluate, and optimize machine learning models using appropriate metrics and techniques.
• Deploy and maintain machine learning models in production environments, ensuring scalability and reliability.
• Collaborate with cross-functional teams to integrate machine learning solutions into existing products and services.

Qualifications

To land this role you will need:

• A self-sufficient modeler with hands-on experience with deep learning models, with application in finance/time series models is a plus.
• Strong theoretical and practical understanding of machine learning and deep learning algorithms.
• Proficiency in Python and relevant machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Excellent problem-solving, analytical, and communication skills.
• Ability to work independently and as part of a team.  
• Able to work part time for 3-6 months

Education / Certification Requirements: 

• Master's or PhD degree in Computer Science, Statistics, Mathematics, or a related field.

Working environment:

• Hybrid