Job Title - Data Scientist -AI/ML SME
12 – 24 Months
Phone and Skype
Remote/East Coast
Years of Exp.: 13+ years exp.
Job Description:
Data Scientist & AI/ML SME
Role Overview
Seeking expertise to support our cybersecurity risk team by streamlining processes, improving risk detection, and enhancing decision-making through data-driven solutions. This role focuses on automating workflows, building predictive models, and extracting actionable insights from complex security and risk datasets.
Required Skills and Qualifications
o Experience: 5+ years.
o Programming: Proficiency in multiple scripting / coding languages, and API use.
o Technology Stack: Tools are listed in priority order. Experience with Microsoft Power Tools, GRC tools, Databricks, Splunk, SharePoint, ServiceNow ticket generation, Okta automation, cloud platforms (AWS, Google Cloud Platform, Azure), AI/ML libraries, database administration, and low-code/no-code tools. Experience with an RPA (Robotic Process Automation) platform is a plus.
o Data Analysis: Ability to analyze large datasets, leveraging multiple tools, to uncover patterns for process optimization. Ability to analyze and troubleshoot complex data ingestion and parsing issues.
o Process Management: Knowledge of Business Process Management (BPM) and workflow optimization.
o Education: Bachelor''s degree in Computer Science, IT, a related field, or equivalent experience.
o Security Experience: Exposure to network security or cybersecurity.
Key Responsibilities
o Solution Design & Development: Create, configure, and deploy automated systems combining AI, ML, RPA bots, Microsoft Power Tools, Databricks, and Splunk to support real-time or near-real-time risk monitoring.
o Process Analysis: Analyze large, complex datasets (e.g., logs, vulnerability scans, threat intelligence) to uncover patterns and anomalies. Understand and analyze repetitive, time-consuming business processes to determine recommended automation solution using Postal tools.
o Technical Implementation: Write and update code, build custom scripts, integrate AI models into existing infrastructure like Splunk, Databricks, ServiceNow, and Microsoft Power Tools to automate manual risk assessment and reporting processes and improve efficiency and accuracy. Build dashboards and visualizations to communicate insights to technical and non-technical stakeholders.
o Maintenance & Troubleshooting: Monitor and optimize automation performance, troubleshoot errors, and ensure system scalability.
o Collaboration: Collaborate with cybersecurity analysts, engineers, and stakeholders to translate business needs into data solutions.
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