Data Scientist

• Gurucul is seeking an innovative analytics thinker for the role of Data Scientist to be part of Gurucul?s Data Science team.
• The candidate will be a key individual contributor, responsible for the design and development of predictive models using the latest technologies in machine learning.
• The ideal candidate will have previous experience in the cybersecurity domain, analyzing large data sets to develop actionable analytics solutions.
• The candidate must also have experience in developing business intelligence solutions to improve operational efficiency, and in using data visualization tools to help in building visualization ideas to present the results to management teams.
• The individual will be responsible for the creation of data models that can be applied for a variety of cybersecurity and fraud use cases. The ideal candidate must be able to pick suitable analytic techniques to address the problem and demonstrate expertise in using various algorithms and other modeling techniques.
• The individual will report directly to Gurucul?s CTO. This position will also provide candidates the opportunity to interact with some of the best brains in information security space, such as Fortune 500 C-level executives, showcase their skills and passion as a Data Scientist in the cybersecurity analytics field.

RESPONSIBILITIES

• Architect, develop, and deploy state-of-the-art predictive and generative AI models for cybersecurity and fraud detection
• Design and implement end-to-end LLM-based pipelines?including prompt engineering, embedding generation, vector search, and retrieval-augmented generation.
• Design and deploy autonomous AI agents that orchestrate end-to-end workflows-automating threat hunting, incident triage etc. using custom agent architecture.
• Build robust data-processing workflows that handle high-velocity streaming and batch data (billions of daily events)
• Select and tune appropriate supervised and unsupervised algorithms (e.g., classification, clustering, anomaly detection) to address diverse security challenges
• Collaborate with offshore and onshore engineering teams to integrate models into production systems and APIs
• Rapidly iterate with product managers and stakeholders on prototypes, proofs-of-concept, and interactive dashboards
• Translate complex analyses into clear data visualizations and executive summaries using BI and front-end visualization tools
• Mentor junior data scientists and share best practices in model development, evaluation, and deployment

Requirements

• MSMS or PhD in Computer Science, Statistics, Applied Mathematics, Engineering, or a related quantitative field
• 5+ years of hands-on experience in applied analytics, predictive modeling, or machine learning?ideally within a cybersecurity or financial-fraud context
• Proven track record with both classical ML (e.g., SVMs, decision trees, regression, clustering) and modern deep-learning/LLM frameworks
• Practical experience designing and deploying LLM-driven solutions (prompt design, fine-tuning, embeddings, vector stores, RAG, MCP Server). Knowledge of finetuning LLM models and MCP Server is a plus.
• Proven experience designing, developing, and deploying autonomous AI agents and orchestration workflows (e.g., with LangChain or similar frameworks).
• Strong programming skills in Python (including popular ML libraries), plus experience with UNIX scripting (Bash, Perl)
• Proven expertise in MySQL, including advanced query authoring, performance tuning (indexes, EXPLAIN plans), stored-procedure development, and database schema design.
• Familiarity with big-data ecosystems (e.g., Spark, Hadoop) and multiple database technologies
• Solid understanding of reinforcement-learning concepts is a plus
• Excellent problem-solving skills, initiative, and ability to juggle multiple projects in a fast-paced environment
• Exceptional oral and written communication skills, with the ability to convey technical concepts to non-technical audiences