Cyber Security

Description: About the Role

We are seeking a motivated Cybersecurity Data Science Contractor with a strong foundation in data science, machine learning, and a demonstrated interest in cybersecurity. This role bridges the gap between advanced data-driven techniques and practical security operations. You will work alongside experienced cybersecurity professionals to analyze security telemetry, develop models for threat detection, and apply modern data science methods to real-world security problems.

Responsibilities
•Support the development of data-driven models to improve detection of threats, anomalies, and insider risks.
•Apply machine learning techniques such as gradient descent, logistic regression, clustering, and neural networks to cybersecurity use cases.
•Perform exploratory data analysis (EDA) on diverse security datasets (endpoint, network, cloud, identity, vulnerability).
•Collaborate with the security operations and threat intelligence teams to design metrics, features, and models that enhance detection and response.
•Contribute to automation workflows, anomaly scoring models, and visualization dashboards for SOC analysts.
•Research and experiment with AI/ML techniques (e.g., embeddings, NLP, anomaly detection) to extract actionable insights from large volumes of security data.
•Present findings and proof-of-concept results to both technical and non-technical stakeholders.

Required Qualifications
• 2-3 years of experience
•Currently pursuing a degree (Bachelors, Master’s, or PhD) in Data Science, Computer Science, Cybersecurity, Applied Math, or related field.
•Strong understanding of machine learning fundamentals (gradient descent, optimization, supervised/unsupervised learning).
•Experience with Python and data science libraries (NumPy, Pandas, scikit-learn, PyTorch or TensorFlow).
•Basic knowledge of cybersecurity concepts such as threats, vulnerabilities, intrusion detection, and MITRE Telecommunication&CK.
•Ability to analyze large datasets and communicate findings clearly.