Senior Data Scientist - Cybersecurity (IAM)

Company Description

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid.

Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.

Job Description

As a Data Scientist on Visa’s Global Business‑to‑Business Identity & Access Management (B2B IAM) team, you will turn authentication, authorization, and directory telemetry into actionable insight. You’ll help build baseline models and analyses for anomaly detection, user/entity behavior analytics (UEBA), and risk‑based access that strengthen MFA journeys and session controls while improving user experience. In partnership with IAM Engineering and Release Engineering, you’ll take work from notebooks to production on ForgeRock‑centric platforms using CI/CD, containerization, and monitoring. You will also explore agentic AI approaches—safe, human‑in‑the‑loop automations that can propose experiments, generate features, triage anomalies, and suggest policy or journey adjustments (e.g., automating onboardings), with audit trails and guardrails. Your contributions will support service reliability and SLA/availability targets and will follow privacy‑by‑design practices aligned to GDPR, PCI DSS, and other audits.

Essential Functions

·         Ingest and prepare IAM telemetry (ForgeRock AM/DS, SAML/OIDC/OAuth events, MFA, sessions, directory logs) for analysis and modeling.

·         Build and evaluate baseline models for anomaly detection, UEBA, and risk scoring, track clear metrics (precision/recall, ROC‑AUC/PR‑AUC).

·         Run focused EDA and A/B tests to tune adaptive journeys and MFA step‑ups for both security and user experience.

·         Engineer features and keep work reproducible (clean notebooks, versioned datasets, lightweight data docs).

·         Package analyses/models for production (Docker and VM’s) and contribute to CI/CD and safe rollouts (e.g., canary) with Release Engineering covering the entire scope of release and dependent functions to execute with PRE teams.

·         Set up basic monitoring for data/model quality, drift, and errors, create simple dashboards/alerts.

·         Partner with IAM engineers to turn insights into policy/rule changes (risk‑based access, session controls) and validate impact on SLO/SLA.

·         Explore agentic AI (human‑in‑the‑loop) to propose experiments, generate features, and triage anomalies—within audit and safety guardrails.

·         Apply privacy‑ and security‑by‑design (minimize personal data, pseudonymize) aligned to GDPR, PCI DSS, and other audits.

·         Document findings clearly and communicate results to technical and non‑technical stakeholders.

This is a hybrid position. Expectation of days in office will be confirmed by your Hiring Manager.

Qualifications

Basic Qualifications
• 2+ years of relevant work experience and a Bachelors degree, OR 5+ years of relevant work experience

Hands-on with:
• Python for data science (pandas, NumPy, scikit-learn) and SQL for data preparation and analysis.
• Exploratory Data Analysis (EDA), basic supervised learning (logistic/trees), simple anomaly detection, model evaluation (precision/recall, ROC-AUC/PR-AUC).
• Preparing IAM-style telemetry (e.g., authentication/authorization, MFA, session, directory logs) for analysis and feature engineering.
• Building clear dashboards/visualizations (e.g., in Splunk, Elastic/Kibana, or Grafana).
• Exposure to:
• Identity and access management concepts: SAML 2.0, OpenID Connect, OAuth 2.0, MFA modalities, high-level session management, willingness to learn ForgeRock AM/DS telemetry.
• MLOps and release engineering basics: Git and pull requests, CI/CD concepts, Docker fundamentals, and safe rollout patterns (e.g., canary) under guidance.
• Monitoring for data/model quality (drift, latency, errors) and creating simple alerts.
• Ways of working:
• Experience collaborating with cross-functional, globally distributed teams.
• Working knowledge of Agile/Scrum, familiarity with issue tracking and release workflows in Jira.
• Excellent verbal and written communication, ability to explain findings simply to non-technical stakeholders.
• Security and compliance mindset:
• Awareness of privacy- and security-by-design principles (data minimization, pseudonymization, access control) and why GDPR, PCI DSS, and ISO/IEC 27001 m