Associate Data Scientist

Key Responsibilities

• Develop analytics to address security concerns and enhance organizational security capabilities.
• Collaborate with Data Engineers to translate security-focused algorithms into practical solutions.
• Participate in technical teams for the development, deployment, and application of analytics, including predictive and prescriptive analytics.
• Perform exploratory and targeted data analyses using descriptive statistics to identify security patterns and anomalies.
• Design and implement security-focused analytics pipelines using MLOps practices, generative AI, and agent-based architectures for threat detection and response.
• Work with data engineers on data quality assessment, cleansing, and the development of security-related data pipelines.
• Contribute to data engineering efforts to refine data infrastructure for scalable and efficient security analytics.
• Generate reports, annotated code, and project artifacts to document and communicate work and outcomes.
• Share and discuss findings within a SAFe Agile delivery model team.

Qualifications

Basic Qualifications

• Master's degree OR Bachelor's degree and 2 to 6 years of experience with analytic software tools or languages (e.g., SAS, SPSS, R, Python).

Preferred Qualifications

• Experience with analytic software tools or languages (e.g., SAS, SPSS, R, Python).
• Experience applying generative AI and agent-based systems to cybersecurity use cases, such as automated threat detection, response orchestration, and security analysis.
• Demonstrated skill in applied analytics, descriptive statistics, feature extraction, and predictive analytics on industrial datasets.
• Strong foundation in machine learning algorithms and techniques.
• Experience in statistical techniques, hypothesis testing, regression analysis, clustering, and classification.

Good-to-Have Skills

• Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Outstanding analytical and problem-solving skills; ability to learn quickly; excellent communication and interpersonal skills.
• Experience with data engineering and pipeline development.
• Experience in analyzing time-series data for forecasting and trend analysis.
• Experience with cloud platforms like AWS, Azure, or Google Cloud.
• Experience with the Databricks platform for data analytics and MLOps.
• Experience working in product teams and Agile environments.

Professional Certifications (Preferred)

• Any AWS Developer certification.
• Any Python and ML certification.
• Any SAFe Agile certification.

Soft Skills

• Initiative to explore alternate technologies and approaches.
• Skilled in problem breakdown, documentation, and effort estimation.
• Excellent analytical and troubleshooting skills.
• Strong verbal and written communication skills.
• Ability to work effectively with global, virtual teams.
• High degree of initiative and self-motivation.
• Ability to manage multiple priorities successfully.
• Team-oriented, with a focus on achieving team goals.