Data Science Intern
Data Science Intern
About Arkham
Arkham is a Data & AI Platform—a suite of powerful tools designed to help you unify your data and use the best Machine Learning and Generative AI models to solve your most complex operational challenges.
Today, industry leaders like Circle K, Mexico Infrastructure Partners, and Televisa Editorial rely on our platform to simplify access to data and insights, automate complex processes, and optimize operations. With our platform and implementation service, our customers save time, reduce costs, and build a strong foundation for lasting Data and AI transformation.
About the Role:
As Arkham continues to grow and demonstrate a strong product-market fit, we are excited to expand our AI team with the addition of a Data Science Intern. This role offers a unique opportunity for new data scientists to immerse themselves in a dynamic and innovative environment.
As a Data Science Intern, you will work closely with our experienced team, including our Head of AI. Your role will encompass everything from deploying Generative AI solutions for our financial services customers to aiding our infrastructure clients in optimizing their operations using time series forecasting and anomaly detection models.
This position offers a blend of learning and practical application. You will gain hands-on experience with our platform, diving into real-world challenges and assisting in crafting scalable solutions. Your contributions will not only provide valuable support to our team but also offer you a chance to understand and address the needs of a growing market.
Core Responsibilities:
- Support in Designing and Implementing ML and Generative AI Algorithms: Assist in the creation and development of machine learning and AI models, gaining exposure to both the application of existing models and the innovation of new methodologies.
- Testing and Validation Assistance: Help ensure the accuracy and reliability of our models by participating in various testing methodologies, thereby learning to evaluate the performance and reliability of the AI Platform under different scenarios.
- Documentation Support: Assist in developing clear documentation that explains methodologies, algorithms, and analytics insights derived from ML and AI models.
- Data Visualization: Create visual representations of data trends and model outcomes, learning how effective visualizations can communicate complex ideas to a broader audience, including those without a technical background.
What We Value:
- A keen interest in technology and belief in its transformative power.
- Strong communication, writing, and analytical skills developing in a team environment.
- Eagerness to learn and contribute in a fast-paced, innovative setting.
- Adaptability and resilience, with a willingness to tackle complex challenges.
What We Require:
- Educational Background: Currently pursuing or recently completed a Bachelor's degree in a quantitative field such as Science, Statistics, Computer Science, or a similar discipline. Students who are in the final stages of their degree or have a strong academic record in relevant subjects are encouraged to apply.
- Foundational Mathematical and Statistical Knowledge: A strong foundation in mathematics, particularly in statistical models and techniques.
- Technical Skills:
- Strong knowledge of Python and SQL.
- Familiarity with traditional machine learning models, supervised and unsupervised.
- Familiarity with forecasting models and Generative AI.
- Basic understanding of cloud platforms like AWS is a plus.
- Some experience or familiarity with software version control tools such as GIT.