Senior Data Scientist – Machine Learning & LLM

About the role

We are seeking a highly skilled and motivated Senior Data Scientist to join our talented team. In this role you will develop and optimize our machine learning and large‑language‑model capabilities, collaborating with software engineers, security researchers, and product management to design, develop, evaluate, and deploy models that address complex cybersecurity challenges.

Key responsibilities

• Analyze large, complex datasets to identify patterns and trends that could indicate potential security threats.
• Collaborate with cybersecurity researchers to develop solutions that leverage advanced machine learning and data analytics.
• Design, develop, and evaluate ML and LLM‑based solutions—including classification, NLP, and security‑focused models—from experimentation through production.
• Develop and optimize LLM techniques such as prompting, retrieval, embeddings, RAG, and fine‑tuning where appropriate.
• Design robust evaluation methodologies and experiments for classification and LLM‑based systems using appropriate metrics.
• Stay up to date with advancements in machine learning, NLP, LLMs, and related technologies and assess their applicability to real‑world cybersecurity problems.
• Collaborate with software and data engineers to integrate ML and LLM solutions into scalable production systems.
• Take ownership of complex data‑science problems from definition through implementation and evaluation.

Required profile

• Bachelor’s degree in Computer Science, Engineering, Statistics, Mathematics, or a related field (Master’s/PhD a plus).
• 5+ years of hands‑on experience in data science, machine learning, or a related field.
• Strong understanding of machine learning and deep learning with experience developing and evaluating classification models.
• Hands‑on experience with NLP and text classification, including NER, model training, and fine‑tuning using both traditional and modern LLM approaches.
• Strong proficiency in Python; experience with PySpark and Databricks is a plus.
• Experience developing and evaluating LLM‑based applications, including prompt engineering, embeddings, vector search, and vector databases.
• Familiarity with commercial and open‑source LLM frameworks such as OpenAI models and the Hugging Face ecosystem.
• Proven ability to work with highly imbalanced datasets, select appropriate evaluation metrics, and optimize models for precision/recall trade‑offs.
• Excellent analytical, problem‑solving, communication, and collaboration skills.

Required skills

• Python
• PySpark
• Databricks
• Natural Language Processing (NLP)
• Named Entity Recognition (NER)
• Large Language Models (LLMs)
• OpenAI models
• Hugging Face ecosystem
• Prompt engineering
• Embeddings and vector search
• Vector databases
• Model fine‑tuning and Retrieval‑Augmented Generation (RAG)