Data Scientist, Sr. - Cybersecurity
About the Company
Truelogic is a New York-headquartered provider of nearshore staff augmentation services, partnering with U.S. companies on technology projects and digital transformation initiatives. Its team of more than 600 technology professionals across Latin America works with businesses ranging from startups to established enterprises. About the Client The client is a growing technology company focused on helping organizations adopt and manage artificial intelligence securely at scale. Its platform helps enterprises monitor AI interactions, protect sensitive information, and apply security and governance controls across modern AI applications, including large language models and AI-powered agents.
About the Role
Truelogic is seeking a Senior Data Scientist to join the client’s core AI team. This hands-on role focuses on developing, training, evaluating, and optimizing natural language processing (NLP) models that detect risks in AI interactions, including sensitive-data exposure, unsafe content, and malicious prompts. You’ll work across data curation, synthetic data generation, transformer-based models, and evaluation pipelines to improve the reliability and efficiency of AI security solutions. The role involves close collaboration with engineering and AI teams to turn experiments into production-ready systems.
Key Responsibilities
Build, curate, clean, and maintain datasets for NLP and AI security use cases, including safe and unsafe prompts, sensitive-data exposure scenarios, and adversarial examples. Generate and augment synthetic datasets using large language models to cover edge cases and improve model robustness. Train, fine-tune, and evaluate NLP and transformer-based models for real-time risk detection and classification. Develop and improve custom classifiers and Named Entity Recognition (NER) models to identify sensitive or relevant information. Design evaluation pipelines and benchmarks to measure model quality, accuracy, false positives, and performance. Experiment with different modeling approaches and improve models as new use cases and AI-related threats emerge. Optimize models and inference workflows for production environments where speed and efficiency are essential. Collaborate with engineering and AI teams to move research and experiments into reliable production solutions. Analyze model performance and datasets to identify gaps, edge cases, and opportunities for improvement. Contribute to practical AI/ML workflows, documentation, and engineering best practices. Required Qualifications 4+ years of professional experience as a Data Scientist, Machine Learning Engineer, or in a closely related role. Strong hands-on experience with NLP, transformer-based models, and modern language-model architectures. Strong programming skills in Python. Experience with machine learning and deep learning frameworks such as PyTorch, TensorFlow, or similar technologies. Experience with libraries and ecosystems such as Hugging Face and scikit-learn. Practical experience training, fine-tuning, or adapting machine learning models for real-world applications. Experience with NER, tokenization, text classification, or other NLP techniques. Strong data preparation and analysis skills using Pandas or similar tools. Experience designing model evaluations, benchmarks, and experiments to assess model quality and reliability. Understanding of model performance and inference optimization techniques. Familiarity with AI security concepts, including prompt injection, sensitive-data and personally identifiable information (PII) exposure, adversarial inputs, and data privacy. Strong problem-solving skills and the ability to work independently on ambiguous machine learning challenges. Location & Work Arrangement Work Arrangement: 100% remote Employment Type: Not specified Salary & Benefits Compensation: Highly competitive pay in USD; a specific salary range is not provided. Benefits include: Paid time off Flexible work arrangements focused on results and autonomy Opportunities to work on technology projects with leading U.S. companies A culture that supports well-being and work-life balance Engagement activities and collaboration with a global, multicultural team of more than 600 professionals across 25+ countries