Security Analyst

Build & Fine-Tune Detections: Design, build, and optimize detection rules and risk models to identify emerging fraud vectors while fine-tuning alert thresholds to minimize false positives.

Drive Product & Threat Analytics: Perform Exploratory Data Analysis (EDA), track core product/risk KPIs, and deliver data-driven insights that directly influence product strategy.

Escalation & Optimization: Act as an analytical escalation point for high-stakes enterprise client investigations, providing tailormade analytics to improve detection performance.

Actionable Visualizations: Translate complex data trends into clear dashboards and executive-ready reports that drive action across internal and external stakeholders.

AI & Automation Vision: Configure and deploy AI Agents & Skills within analytical workflows to serve as a key productivity multiplier for the team.

Cross-Functional Collaboration: Partner closely with Product and Analytics teams to support new feature rollouts and strategic decision-making.

2+ years of experience as a Data Analyst / Fraud Analyst / Security Data analyst in a fast-paced, data-rich SaaS environment.

Detection & Analytics Focus: Proven experience in analyzing security/fraud data, building detection logic, and performing Exploratory Data Analysis (EDA).

Strong Tech Stack: Proven expertise in BigQuery and advanced SQL. Hands-on experience with Grafana (or modern visual analytics tools).

Programming: Solid familiarity with Python (Pandas/NumPy) for data manipulation and analysis.

Communication & Stakeholder Management: High verbal and written communication skills in English—capable of leading discussions and presenting complex analytical findings to Enterprise clients and internal leaders.

Problem-Solving & Agility: A proactive mindset with a proven ability to multitask and turn complex data into clear action items.

Education: BA/BS in Statistics, Industrial Engineering, Operations Research, Computer Science, Economics, or a related quantitative field.