Data Scientist II

Title: Data Scientist II Location: REMOTE

Responsibilities:
Plays a crucial role in ensuring the ethical, responsible, and compliant development and deployment of AI systems, particularly those that impact human behavior.
Use artificial intelligence (AI) and machine learning (ML) to analyze user and entity behavior within a network to identify and mitigate cyber threats.
Design and implement behavioral analytics models to surface anomalies and indicators of insider risk across multiple structured and unstructured data sources.
Develop and refine risk scoring algorithms which prioritize users or events based on observed patterns, contextual risk factors, and deviations from baselines.
Integrate and transform data from tools, systems, and logs to create unified risk models which support investigative workflows.
Analyze data to identify patterns, develop theories and models to explain behavior, and design interventions to promote positive change.
Identify unusual employee or contractor activity that could indicate malicious intent.
Gather and prepare diverse behavioral datasets, ensuring accuracy and completeness from sources like website interactions, app usage, customer feedback, and other digital channels.
Conduct exploratory data analysis to identify behavioral trends and precursors which correlate with increased risk profiles.
Create reports, dashboards, and visualizations to clearly communicate findings and insights to stakeholders, including non-technical audiences
Enhance IRO s ability to surface anomalies, prioritize potential risks/threats, and provide decision support.

Technical Skills:
Strong analytical and problem-solving abilities. The ability to identify and assess potential behavioral risks in AI systems, analyze data, and develop effective mitigation strategies is crucial.
Proficiency in relevant tools. Familiarity with AI frameworks (like TensorFlow, PyTorch), cloud platforms (like AWS), and programming languages (like Python) can be highly beneficial.
Strong analytical and communication skills are vital to effectively navigate the complexities of the AI evolving field.
Apply statistical modeling, machine learning, and data fusion techniques to diverse cybersecurity and organizational data.
Proficiency in languages like Java, C++, Python, and SQL.
Strong statistical and analytical foundation, including knowledge of anomaly detection, time-series analysis, and clustering techniques.
Knowledge & experience with API development and automation
Familiarity with cybersecurity data sources and insider threat indicators, especially UEBA, DLP, system logs, and identity data.
Problem-solving Skills and a knack for using data to address business challenges and identify opportunities for improvement.
Data visualization skills using tools like Tableau, Power BI, or Ploy for communicating insights to non-technical stakeholders.
Evaluate programs, disseminating findings, consulting and collaborating with others, and adhering to ethical standards.

Preferred Qualifications:
A degree from an accredited College/University in the applicable field of services is required. If the indiviual's degree is not in the applicable field then four additional years of related experience is required.
A minimum of eight (8) years relevant experience.
Experience in risk management, compliance, or a related field, with specific experience in AI or machine learning.
3+ years of experience in AI concepts and technologies. This includes familiarity with machine learning algorithms, data processing, and AI system design.
Certifications focused on AI security, governance, and development.