Who We Are:

TradeStation is an online brokerage firm seeking to level the playing field for self-directed investors and traders, empowering them to claim their individual financial edge.  At TradeStation, we're continuously pushing the boundaries of what's possible, encouraging out-of-the-box thinking and relentless search for innovation.

What We Are Looking For:

The Data Engineering Intern will contribute to the development, testing, and automation of data pipelines and workflows within our data engineering and AI ecosystems. This role offers the opportunity to work with cutting-edge technologies, including machine learning and AI tools, while developing scalable and automated solutions. The intern will collaborate closely with the team to ensure high-quality deliverables, implement AI-driven enhancements, and apply best practices in data engineering and AI integration.

What You’ll Be Doing:

• Test new features and validate the functionality of data pipelines, AI models, and engineering solutions
• Develop and automate testing suites for data engineering workflows and AI-driven applications to ensure reliability and performance
• Assist in designing and implementing frameworks, fixtures, and best practices for data engineering and AI solutions
• Contribute to the development and deployment of AI models and algorithms within data pipelines
• Collaborate with data engineers and AI specialists to identify opportunities for leveraging machine learning and AI tools
• Troubleshoot and resolve issues in data workflows, AI models, and automation processes

The Skills You Bring:

• Strong analytical and problem-solving skills with a passion for data, technology, and AI
• Familiarity with one or more programming languages (e.g., Python, SQL, or similar) and AI frameworks or libraries (e.g., TensorFlow, PyTorch, or scikit-learn)
• Basic understanding of data engineering concepts such as ETL processes, data pipelines, or big data tools
• Exposure to AI concepts, including machine learning, natural language processing, or computer vision
• Ability to work collaboratively in a team environment and take initiative on tasks
• Interest in learning about AI integration in data engineering, automation, and best practices

Minimum Qualifications:

• Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Data Engineering, Data Science, Artificial Intelligence, or a related field
• Experience with programming languages such as Python, SQL, or similar
• Basic knowledge of data engineering concepts, including ETL processes, data pipelines, and databases
• Familiarity with AI or machine learning concepts and libraries (e.g., TensorFlow, PyTorch, scikit-learn)

Desired Qualifications:

• Experience with big data tools and platforms, such as Apache Spark, Hadoop, or Databricks
• Familiarity with cloud platforms like AWS or Azure
• Hands-on experience with version control systems (e.g., Git)
• Exposure to MLOps practices, including deploying and monitoring machine learning models
• Experience with data visualization tools (e.g., Tableau, Power BI) or Python libraries (e.g., Matplotlib, Seaborn)
• Understanding of data governance, security, and compliance practices

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