Data Science Intern

Bitdefender

Bitdefender is a cybersecurity leader delivering best-in-class threat prevention, detection, and response solutions worldwide. Guardian over millions of consumer, enterprise, and government environments, Bitdefender is one of the industry’s most trusted experts for eliminating threats, protecting privacy, digital identity and data, and enabling cyber resilience. With deep investments in research and development, Bitdefender Labs discovers hundreds of new threats each minute and validates billions of threat queries daily. The company has pioneered breakthrough innovations in antimalware, IoT security, behavioral analytics, and artificial intelligence and its technology is licensed by more than 180 of the world’s most recognized technology brands. Founded in 2001, Bitdefender has customers in 170+ countries with offices around the world. For more information, visit https://www.bitdefender.com

About the Role

As part of the Data Science team, you will develop and deploy models by leveraging the best tools and approaches to address business needs. You will experiment with different technologies and propose the best approaches to achieve your goals, working closely with the Data Analysis, Data Engineering, and Data Warehousing teams. This entry-level role assists with data preparation, evaluation, and refinement of LLM-based systems.

Responsibilities

• Assist in data preparation, exploration and model tuning for LLM projects.
• Contribute to implementation and optimization of language-model applications (prompt engineering, retrieval, agent workflows).
• Write clean, well-documented code following best practices.
• Summarize key findings to support stakeholder understanding.

Experience requirements

• Experience with at least one of: APIs for embeddings and text generation / deep learning frameworks such as PyTorch or TensorFlow.
• Demonstrated Python proficiency with emphasis on data science and machine learning applications.
• Solid understanding of statistics, probability, and experimental methods.
• Basic understanding of version control systems such as Git.

Nice to have

• Ability to write and interpret SQL for data analysis and transformation.
• Familiarity with asynchronous execution and managing concurrent LLM workflows.
• Experience working with both structured and text data.

Education

• Currently pursuing or already completed a Bachelor's degree in Computer Science, Engineering, Statistics, Mathematics, or a related field