Senior Software Engineer - Data Scientist

Data Scientist Generative AI & NLP(Cybersecurity Products)

Experience: 35 Years
Employment Type: Full-time
Location: Pune

Role Overview

We are seeking a Data Scientist to workacross multiple cybersecurity products , applying Generative AI, NLP, and machine learning to enhance detection, intelligence, and automationcapabilities.
This role combines applied research, experimentation, and hands-onengineering , with a clear focus on taking ideas from prototype toproduction in an enterprise product environment.

You will work on security problemsinvolving large-scale, noisy, and adversarial data , collaboratingclosely with product, engineering, and security research teams.

Key Responsibilities

• Design and implement GenAI and NLP solutions across multiple cybersecurity products and use cases
• Build and evaluate LLM-based pipelines (RAG, embeddings, fine-tuning, prompt strategies)
• Conduct applied research : experiment with new models, techniques, and architectures, and assess their product viability
• Develop production-ready ML pipelines , from data preprocessing to model deployment and monitoring
• Work with structured and unstructured security data (logs, alerts, threat feeds, reports)
• Partner with product managers and engineers to align ML outcomes with product requirements and performance SLAs
• Continuously improve model accuracy, explainability, and robustness

Required Skills & Experience

• 35 years of experience in Data Science / Machine Learning roles
• Strong programming skills in Python with hands-on model development experience
• Solid understanding of ML fundamentals (classification, clustering, anomaly detection, evaluation metrics)
• Practical experience with NLP and Generative AI , including:
• Transformer models and embeddings
• LLM fine-tuning or adaptation techniques
• Frameworks such as Hugging Face, LangChain, LlamaIndex
• Experience working with large, real-world datasets and imperfect data
• Ability to balance research exploration with engineering discipline
• Familiarity with Responsible AI, data privacy, and governance

Cybersecurity Domain Expectations

• Working knowledge of core cybersecurity concepts:
• Threat intelligence, malware, phishing, endpoint/network security
• Familiarity with security data and standards:
• IOCs, MITRE ATT & CK, STIX/TAXII, SIEM data
• Understanding that security ML systems must prioritize:
• Low false positives
• Explainability
• Resilience to adversarial behavior

Enterprise & Product Mindset

• Experience contributing to productized ML systems , not just notebooks
• Understanding of model lifecycle management , versioning, and monitoring
• Comfort working in cross-team, multi-product environments
• Ability to document research findings and technical decisions clearly