Data Scientist in Canada Creek, Nova Scotia at Jobgether

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Data Scientist in Canada.

This role focuses on building scalable data models and analytical frameworks to unify and interpret complex vulnerability and security datasets across multiple systems. You will work in a highly data-driven environment where security, risk, and engineering teams rely on your insights to understand exposure trends and systemic weaknesses. The position involves transforming fragmented vulnerability data into consistent, query-ready structures that support ongoing monitoring and reporting. You will also design quantitative approaches to measure risk posture and track changes over time with precision. A key part of the role is delivering clear, actionable reporting that helps stakeholders prioritize remediation efforts effectively. You will contribute to deep-dive analyses that uncover root causes behind vulnerability accumulation and control gaps. The environment is collaborative, technical, and focused on improving security outcomes through high-quality data insights.

• Design and implement scalable data models that integrate vulnerability data across multiple systems, ensuring consistency and performance for analysis and reporting.
• Standardize and normalize heterogeneous vulnerability datasets into structured, queryable formats suitable for ongoing analytics.
• Develop quantitative methodologies to measure vulnerability exposure, risk posture, and trend evolution over time.
• Build and maintain weekly reporting outputs that highlight key metrics, trends, and exposure insights for stakeholders.
• Conduct deep-dive analyses to identify root causes of vulnerability accumulation and uncover systemic security or control gaps.
• Collaborate with vulnerability management, risk, and engineering teams to define KPIs, reporting needs, and analytical priorities.

• 7+ years of experience in data science, analytics, or quantitative modeling, ideally within security, risk, or vulnerability management domains.
• Strong proficiency in SQL, relational data modeling, and Python for data analysis, transformation, and automation.
• Experience working with large-scale, complex datasets and building reliable data pipelines or analytical models.
• Solid understanding of data modeling principles, especially as applied to security or risk-related data.
• Ability to translate complex technical findings into clear, actionable insights for both technical and non-technical stakeholders.
• Preferred experience in cybersecurity or vulnerability management, including familiarity with CVEs and severity/priority frameworks.
• Exposure to data governance, data quality practices, and dashboarding tools such as Power BI or Tableau.

• Competitive compensation package aligned with experience and market benchmarks.
• Remote-friendly work setup with flexibility in how and where you work.
• Opportunity to work on high-impact security and risk analytics problems at scale.
• Collaborative, cross-functional environment with technical and domain experts.
• Exposure to modern data tooling, security frameworks, and advanced analytics practices.
• Professional growth opportunities in data science and cybersecurity domains.