In this contingent resource assignment, you may: Consult on complex initiatives with broad impact and large-scale planning for Information Security Engineering.
Review and analyze complex multi-faceted, larger scale or longer-term Information Security Engineering challenges that require in-depth evaluation of multiple factors including intangibles or unprecedented factors.
Contribute to the resolution of complex and multi-faceted situations requiring solid understanding of the function, policies, procedures, and compliance requirements that meet deliverables.
Strategically collaborate and consult with client personnel.
Required Qualifications:
5+ years of Information Security Engineering experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education.
The Artificial Intelligence and Data Science Engineer is a senior, hands-on technical role responsible for developing and operationalizing AI, machine learning, and advanced analytics solutions that enhance the organization's cybersecurity defense capabilities.
This role focuses on applying data science and AI techniques to security telemetry, automation, and cyber risk insights while ensuring solutions are secure, scalable, and production ready.
The engineer works closely with cybersecurity operations, data engineering, and cloud teams to deliver impactful, data driven security outcomes.
Key Responsibilities:
Design, build, and deploy machine learning and advanced analytics solutions for cybersecurity use cases such as threat detection, anomaly detection, and predictive risk analysis.
Develop AI driven capabilities, including automation and generative AI solutions, to support security investigation, triage, and reporting.
Analyze and model large volumes of security data from enterprise, cloud, identity, and endpoint platforms.
Support cybersecurity metrics, dashboards, and insights used by operational teams and leadership.
Apply secure engineering and data handling practices to ensure compliance with security, privacy, and regulatory requirements.
Partner with cross functional teams across cybersecurity, IT, data, and cloud platforms to integrate AI and analytics solutions.
Act as a senior technical contributor and mentor, supporting best practices in data science, AI, and security engineering.
Required Qualifications:
5+ years of experience in cybersecurity, data science, analytics, machine learning, or related technical fields.
Strong hands-on experience with Python, SQL, and common data science or ML frameworks.
Experience working with security telemetry and platforms such as SIEM, EDR, cloud, or identity systems.
Demonstrated experience deploying analytics or ML solutions into production environments.
Solid understanding of cybersecurity principles, threats, and defensive technologies.
MUST HAVE:
AI engineering: Agentic AI frameworks (vertex), MCP, multi-agent orchestration, LLM API, RAG
Data Science: Lakehouse Architecture, Delta Lake, Iceberg, Snowflake, Databricks, Bigquery, Airflow, ETL, Quantitative Analysis, SQL, Python, PowerBI
Preferred Qualifications:
Experience with generative AI or advanced automation in security or operational environments.
Familiarity with cloud platforms such as Azure, AWS, or GCP.
Knowledge of cybersecurity frameworks including NIST, MITRE Telecommunication&CK, or Zero Trust.
Relevant security, cloud, or AI/ML certifications.
Financial Services Preferred
EEO:
"Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of - Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans."