Research Sr. Data Scientist – NLP and LLM Data

• Research Sr. Data Scientist – NLP and LLM Data

Research Sr. Data Scientist – NLP and LLM Data

About Equixly

Equixly is an Italian cybersecurity company founded to revolutionise API security through proprietary artificial intelligence and machine learning algorithms. Our platform automates the API Security Testing process, enabling companies to identify deep vulnerabilities rapidly, scalably, and continuously.

On a strong growth trajectory, we are building out our AI Team with talented engineers and scientists who want to work on real, production-grade LLM systems and high-complexity technical challenges at the cutting edge of applied AI.

The role

We are looking for a Research Senior Data Scientist to join the AI Team and contribute to the development, analysis, curation, and evaluation of the data used to train and improve Equixly’s AI systems.

This role sits at the intersection of data science, machine learning, NLP, LLM evaluation, and applied AI. You will work on data quality, evaluation methodology, statistical analysis, and data-centric improvements for models used in real cybersecurity products.

This is a high-impact position with direct influence on the quality, reliability, and performance of the models that power our platform. You will report to the Head of AI.

What you will do

Your key responsibilities will include:

Design, analyse, curate, and improve datasets for LLMs, NLP systems, classifiers, and agentic AI workflows.

Support the preparation of high-quality data for model training, evaluation, benchmarking, and continuous improvement.

Define data quality standards, labelling principles, evaluation protocols, and reproducible analysis practices.

Analyse model behaviour, errors, edge cases, and failure modes to identify opportunities for improvement.

Collaborate with AI engineers and researchers to connect data decisions with model performance, robustness, and production behaviour.

Document datasets, experiments, evaluation methodology, and key findings clearly and rigorously.

Stay aligned with the state of the art in data-centric AI, NLP, LLM evaluation, and model post-training.

What we are looking for

Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Statistics, Applied Mathematics, Physics, Engineering, or a closely related scientific discipline.

PhD preferred, especially in machine learning, NLP, data science, statistics, or related areas.

At least 5 years of professional or research experience in data science, machine learning, NLP, LLM evaluation, or closely related fields.

Strong scientific and analytical background, with solid knowledge of statistics, probability, experimental design, and quantitative evaluation.

Proven experience working with machine learning or NLP datasets, including data preparation, analysis, validation, and quality assessment.

Strong Python skills and practical experience with modern data science and machine learning workflows.

Familiarity with LLMs, NLP systems, model evaluation, supervised fine-tuning, preference data, or related post-training workflows.

Ability to analyse complex results, identify data-related issues, and communicate findings clearly to technical and non-technical stakeholders.

Good written and spoken English.

Nice to have

Scientific publication record in machine learning, NLP, data science, statistics, cybersecurity, or related areas.

Experience in cybersecurity, API security, vulnerability analysis, agentic AI, or reasoning models.

Experience with LLM evaluation, data-centric AI, reproducible experiments, or MLOps workflows.

Familiarity with data quality techniques such as noisy-label detection, deduplication, dataset validation, or bias analysis.

What we offer

A stimulating and dynamic work environment in an innovative startup at the intersection of cybersecurity and applied AI.

Real opportunities for professional growth and impact: you will join a fast-evolving AI Team working on production-grade LLM systems and high-complexity technical problems.

Direct contribution to Equixly’s AI strategy, improving the quality, reliability, and performance of the data and models at the core of our platform.

Competitive compensation commensurate with experience, plus company benefits.