Data Scientist

Data Scientist, Level 2 (Intermediate) Functional Description: In addition to being responsible for applying data science techniques for cybersecurity solutions. May extract, transform, load, analyze and interpret relevant IA (information assurance) data for timely analytic use, provide reports on any associated patterns, anomalies, and potential security concerns, and support relevant data management. May use machine learning and statistical approaches based on the analysis of the dataset. May prepare visualizations including dashboards, graphs, and presentations to communicate cybersecurity recommendations. May conduct and/or support data engineering and data management. May assist with the selection of appropriate analytical approaches towards automation. Reviews and defines requirements for data science cybersecurity approaches. Tools used to include the following or equivalent: AWS, Spark, Kafka, Tableau, Python (e.g., TensorFlow and PyTorch), R (e.g., tidyverse, RShiny), Splunk. Familiarity with the Agile (i.e., Scrum, Jira, Confluence) or equivalent project management process preferred, the Level 2 Data Scientist (Intermediate) is responsible for designing data science techniques for cybersecurity solutions. May adjust and create machine learning and statistical approaches based on the analysis of the dataset. May analyze visualizations including dashboards, graphs, and presentations to communicate cybersecurity recommendations. May conduct data engineering and data management. May lead with the selection of appropriate analytical approaches towards automation. Reviews and defines requirements for data science cybersecurity approaches.

Data Scientist Level 3 (Senior) Functional Description: In addition to achieved duties described in Level 2, the Data Scientist Level 3 is responsible for overseeing data science techniques for cybersecurity solutions. May lead teams to extract, transform, load, analyze and interpret relevant IA (information assurance) data for timely analytic use, provide reports on any associated patterns, anomalies, and potential security concerns, and support relevant data management. May advise machine learning and statistical approaches based on the analysis of the dataset. May present visualizations including dashboards, graphs, and presentations to communicate cybersecurity recommendations. May spearhead data engineering and data management. May advise appropriate analytical approaches towards automation. Establishes requirements for data science cybersecurity approaches.

• Data Scientist Level 2 Qualifications: Bachelor's degree or equivalent and five (5) years of relevant experience in data science, mathematics, statistics, business analytics, or equivalent quantitative field, preferably with exposure to cybersecurity applications and/or operations.
• Includes strong knowledge of data visualizations, large language models (LLMs), and machine learning principles, techniques, and technologies.

Level 3 Data Scientist:

• Data Scientist Level 3 Qualifications: Bachelor's degree or equivalent and seven (7) years of relevant experience in data science, mathematics, statistics, business analytics, or equivalent quantitative field, preferably with exposure to cybersecurity applications and/or operations.
• Includes expert knowledge of data visualizations, large language models (LLMs), and machine learning principles, techniques, and technologies