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Senior Data Scientist - Cybersecurity

Job in Phoenix, Maricopa County, Arizona, 85003, USA
Listing for: Truelogic
Full Time position
Listed on 2026-10-06
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, AI Evaluation
Salary/Wage Range or Industry Benchmark: 140000 - 200000 USD Yearly USD 140000.00 200000.00 YEAR
Job Description & How to Apply Below
About Truelogic

At Truelogic we are a leading provider of nearshore staff augmentation services headquartered in New York. For over two decades, we’ve been delivering top-tier technology solutions to companies of all sizes, from innovative startups to industry leaders, helping them achieve their digital transformation goals.

Our team of 600+ highly skilled tech professionals, based in Latin America, drives digital disruption by partnering with U.S. companies on their most impactful projects. Whether collaborating with Fortune 500 giants or scaling startups, we deliver results that make a difference.

By applying for this position, you’re taking the first step in joining a dynamic team that values your expertise and aspirations. We aim to align your skills with opportunities that foster exceptional career growth and success while contributing to transformative projects that shape the future.

Our Client

A growing technology company focused on helping organizations safely adopt and manage artificial intelligence  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.

Job Summary

We are seeking a Senior Data Scientist to join the core AI team and work hands‑on across data curation, model development, evaluation, and optimization. In this role, you will help build and improve NLP models that identify potential risks in AI interactions, including sensitive‑data exposure, unsafe content, and adversarial or malicious prompts. You will work with modern transformer‑based models and large language model technologies while developing high‑quality datasets and evaluation processes that support reliable, low‑latency AI security solutions.

The ideal candidate combines strong hands‑on experience in NLP, transformers, model training, and data curation with a practical approach to experimentation and production machine learning.

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 LLMs 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 for identifying sensitive or relevant information.

  • Design evaluation pipelines and benchmarks to measure model quality, accuracy, false positives, and performance.

  • Experiment with different modeling approaches and continuously improve models as new use cases and AI‑related threats emerge.

  • Optimize models and inference workflows for production environments where speed and efficiency are critical.

  • Collaborate with engineering and AI teams to move models and experiments from research into reliable production solutions.

  • Analyze model performance and datasets to identify gaps, edge cases, and opportunities for improvement.

  • Contribute to the development of practical AI/ML workflows, documentation, and best practices.

Qualifications and Job Requirements
  • 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, Tensor Flow, or similar.

  • Experience with libraries and ecosystems such as Hugging Face and scikit‑learn.

  • Hands‑on experience training, fine‑tune, or adapting machine learning models for real‑world…

Position Requirements
10+ Years work experience
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