About the role
Data Science Intern
About Arkham Technologies
Arkham Technologies is at the forefront of the Data and AI landscape, providing an innovative platform that integrates advanced tools for data unification and the application of cutting-edge Machine Learning and Generative AI models. Our solutions empower organizations to tackle their most intricate operational challenges efficiently.
Notable industry leaders, including Circle K, Mexico Infrastructure Partners, and Televisa Editorial, leverage our platform to streamline data access, automate intricate processes, and enhance operational efficiency. By utilizing our technology and implementation services, clients not only save time and reduce costs but also lay the groundwork for sustainable Data and AI transformations.
About the Role:
As we continue to expand and solidify our market presence, we are thrilled to welcome a Data Science Intern to our dynamic AI team. This internship presents an invaluable chance for emerging data scientists to engage in a vibrant and innovative atmosphere.
In this role, you will collaborate closely with our seasoned professionals, including our Head of AI. Your responsibilities will range from deploying Generative AI solutions for our financial services sector to assisting infrastructure clients in optimizing their operations through time series forecasting and anomaly detection models.
This internship combines theoretical learning with practical application, offering you hands-on experience on our platform while tackling real-world challenges and contributing to scalable solutions. Your efforts will provide essential support to our team while helping you gain insights into the needs of a rapidly evolving market.
Core Responsibilities:
- Assist in the Design and Implementation of ML and Generative AI Algorithms: Participate in developing machine learning and AI models, gaining insights into both the application of existing models and the development of new methodologies.
- Support Testing and Validation: Ensure the models' accuracy and reliability through various testing methodologies, learning to evaluate the AI Platform's performance across different scenarios.
- Contribute to Documentation: Help create comprehensive documentation that details methodologies, algorithms, and analytical insights derived from ML and AI models.
- Data Visualization: Develop visual representations of data trends and model outcomes, learning to effectively communicate intricate concepts to diverse audiences, including non-technical stakeholders.

