What is the First 90 Days course about?
How to establish trust, align controls to business risk, and lead confidently from day one in a high-expectation environment Each order is checked and updated against the latest insights before delivery. That is why access takes up to 24 hours rather than being instant.
What situation is the First 90 Days for?
Security leaders arrive with deep expertise but face unspoken expectations: aligning risk posture with model-driven decision-making, earning trust across quants and traders, and producing audit-ready evidence fast, all while proving value before skepticism sets in.
Who is the First 90 Days course for?
New or recently hired Head of Security, CISO, or Director of Information Security joining a quantitative trading, hedge fund, or algo-based financial services firm.
What do you take away from the First 90 Days course?
Establish measurable security credibility within the first 30 days Align control design with business-critical systems like trade execution and risk models Produce audit-ready evidence packages without cross-team rework Lead first-risk committee discussions with confidence and clarity Build repeatable onboarding playbooks for future security hires.
How does this map to your situation?
Onboarding as Head of Security First audit cycle preparation Stakeholder alignment across quants, risk, and engineering Long-term influence beyond initial credibility phase.
What's included with your purchase?
12 modules with 12 chapters each (144 chapters) Downloadable templates and worked examples for every module Hand-built implementation playbook delivered alongside course access 30-day money-back guarantee.
What does the First 90 Days cover on delivery and format?
Format: Text-based modules and chapters in the Art of Service learning environment, plus downloadable templates and worked examples for every chapter, plus the hand-built implementation playbook delivered alongside course access. Time investment: Approximately 90 minutes per week over six weeks, designed for completion on weekends or quiet evenings.
How does this compare to the alternatives?
Unlike generic cybersecurity leadership courses, this program focuses exclusively on the unwritten rules, technical nuances, and stakeholder dynamics unique to quantitative finance environments.
Closely related courses: First 90 Days as CISO, AI-Driven Leadership in the First 90 Days.
More answers: what you get with every course, refund policy, all help answers.
A tailored course, built for your situation
First 90 Days: Building Security Credibility in a Quantitative Finance Firm
How to establish trust, align controls to business risk, and lead confidently from day one in a high-expectation environment
Each order is checked and updated against the latest insights before delivery. That is why access takes up to 24 hours rather than being instant.
The situation this course is for
Security leaders arrive with deep expertise but face unspoken expectations: aligning risk posture with model-driven decision-making, earning trust across quants and traders, and producing audit-ready evidence fast, all while proving value before skepticism sets in.
Who this is for
New or recently hired Head of Security, CISO, or Director of Information Security joining a quantitative trading, hedge fund, or algo-based financial services firm
Who this is not for
Junior security analysts, general IT managers, or professionals outside financial services with no exposure to quant environments
What you walk away with
- Establish measurable security credibility within the first 30 days
- Align control design with business-critical systems like trade execution and risk models
- Produce audit-ready evidence packages without cross-team rework
- Lead first-risk committee discussions with confidence and clarity
- Build repeatable onboarding playbooks for future security hires
The 12 modules (with all 144 chapters)
- Identifying high-velocity data pipelines in trading systems
- Recognizing where model inputs become security touchpoints
- Differentiating risk posture for research versus production models
- Tracing data lineage from ingestion to execution
- Assessing third-party risk in vendor-supplied quant libraries
- Reviewing access patterns for quants, traders, and researchers
- Understanding the impact of low-latency requirements on controls
- Auditing ephemeral compute environments used in backtesting
- Evaluating real-time monitoring constraints in high-frequency systems
- Documenting acceptable risk thresholds for algorithmic exposure
- Prioritizing systems based on financial impact, not CVE count
- Creating a living map of the quant attack surface
- Translating model validation requirements into security evidence
- Preparing for audit questions about data provenance and tampering
- Aligning SOC 2 reporting with quant-specific control objectives
- Documenting access reviews for non-human identities in model workflows
- Explaining anomaly detection thresholds in trading contexts
- Justifying control exceptions based on performance constraints
- Mapping NIST 800-53 controls to model lifecycle phases
- Building evidence trails for automated trading decisions
- Handling auditor requests for real-time decision logs
- Demonstrating separation of duties in collaborative quant environments
- Responding to queries about model retraining triggers and security
- Maintaining audit readiness without slowing model deployment
- Speaking the language of statistical significance and error rates
- Positioning security as a risk enabler, not a bottleneck
- Conducting initial meetings that respect quant workflows
- Identifying key influencers within quant research groups
- Addressing concerns about compute overhead from security tools
- Collaborating on secure coding standards for Python and R
- Presenting risk findings using quant-friendly visualizations
- Avoiding compliance jargon in cross-functional discussions
- Co-designing monitoring rules with data scientists
- Acknowledging model uncertainty in risk assessments
- Gaining buy-in for security reviews during sprint planning
- Measuring success by reduced friction, not just policy adherence
- Prioritizing controls based on potential P&L exposure
- Aligning encryption standards with data sensitivity tiers
- Defining access levels for model parameters and weights
- Implementing just-in-time access for production model updates
- Creating exception processes with clear risk trade-offs
- Integrating threat modeling into model development sprints
- Using failure mode analysis to guide control placement
- Documenting rationale for accepting quant-driven risks
- Building automated checks for model input sanitization
- Reviewing container security in CI/CD pipelines for quants
- Enforcing configuration standards in ephemeral compute
- Tracking control effectiveness through quant-relevant KPIs
- Structuring risk reports for time-constrained executives
- Highlighting exposures that could impact trading strategies
- Using quant-like metrics to express security posture
- Avoiding technical depth that obscures business impact
- Framing recommendations around capital protection
- Preparing for pushback on control implementation costs
- Linking security initiatives to firm-wide risk appetite
- Visualizing risk concentration across model portfolios
- Benchmarking posture against peer quant firms
- Explaining cyber risk in terms of value-at-risk (VaR)
- Summarizing third-party risk in portfolio context
- Delivering updates that build, not erode, credibility
- Planning evidence collection before the audit notice arrives
- Identifying repeatable artifacts across compliance frameworks
- Standardizing documentation formats for cross-team use
- Automating evidence capture for access reviews and logs
- Coordinating with legal and compliance on response timing
- Reviewing draft findings with quant leads before submission
- Addressing auditor questions about model-specific controls
- Tracking evidence completeness with real-time dashboards
- Preparing rebuttals for misunderstood technical contexts
- Using templates to ensure consistency across reviewers
- Reducing rework by aligning teams pre-audit
- Closing findings with root cause fixes, not one-offs
- Introducing secure defaults in Jupyter notebook templates
- Reviewing GitHub repositories for hardcoded credentials
- Enforcing dependency scanning in Python and R environments
- Monitoring for unauthorized data exfiltration attempts
- Implementing peer review gates for production model code
- Scanning for known vulnerabilities in quant libraries
- Configuring secure compute environments for backtesting
- Logging and alerting on anomalous model behavior
- Protecting API keys used in market data feeds
- Validating input data ranges to prevent model poisoning
- Controlling access to model training datasets
- Automating security checks in CI/CD pipelines
- Defining incident severity based on market impact
- Creating response playbooks that preserve system availability
- Identifying forensic data sources in low-retention systems
- Coordinating with trading desks during live incidents
- Containing threats without halting algorithmic execution
- Preserving evidence in memory-constrained environments
- Communicating incidents to leadership without panic
- Reviewing post-incident for model-specific attack vectors
- Testing response plans with simulated market conditions
- Documenting trade-offs between security and uptime
- Integrating threat intelligence into trading risk models
- Training on-coming quants in incident reporting
- Tracking regulatory updates from SEC, FINRA, and CFTC
- Mapping DORA requirements to quant infrastructure
- Preparing for MiFID II recordkeeping obligations
- Aligning internal audits with fiscal quarter closes
- Responding to regulator requests for model documentation
- Demonstrating compliance in cloud-based quant environments
- Auditing vendor risk for third-party quant platforms
- Maintaining logs for algorithmic decision trails
- Ensuring data residency aligns with jurisdictional rules
- Reviewing model fairness and bias as a compliance item
- Validating business continuity plans for trading models
- Reporting cyber incidents within mandated timeframes
- Conducting introductory sessions with risk committee members
- Building relationships with chief investment officers
- Collaborating with legal on data usage agreements
- Engaging compliance teams on audit timelines
- Partnering with infrastructure teams on secure deployment
- Educating HR on security hiring for quant roles
- Aligning procurement on vendor security assessments
- Synchronizing with finance on cyber insurance disclosures
- Coordinating with data governance on metadata tagging
- Establishing cross-functional escalation paths
- Creating shared dashboards for risk visibility
- Hosting quarterly alignment workshops across domains
- Defining your credibility milestones by week
- Identifying quick wins with visible business impact
- Scheduling key stakeholder meetings in the first month
- Drafting your first risk committee presentation
- Launching a low-friction security improvement
- Publishing a transparent security update
- Gathering feedback from quant team leads
- Measuring progress through peer validation
- Adjusting priorities based on early signals
- Documenting lessons from initial control rollouts
- Refining messaging based on leadership reactions
- Finalizing your credibility narrative for review
- Institutionalizing security reviews in model lifecycle
- Expanding your influence to adjacent business units
- Mentoring junior security hires in quant contexts
- Contributing to firm-wide risk strategy discussions
- Presenting at internal tech talks on security topics
- Building a repeatable onboarding package for successors
- Evolving controls as new trading strategies emerge
- Advancing security culture through recognition programs
- Integrating threat modeling into new product launches
- Sharing metrics that show security's business value
- Positioning for broader risk leadership roles
- Maintaining relevance as the threat landscape shifts
How this maps to your situation
- Onboarding as Head of Security
- First audit cycle preparation
- Stakeholder alignment across quants, risk, and engineering
- Long-term influence beyond initial credibility phase
Before vs. after
What's included with your purchase
- 12 modules with 12 chapters each (144 chapters)
- Downloadable templates and worked examples for every module
- Hand-built implementation playbook delivered alongside course access
- 30-day money-back guarantee
Delivery and format
- Course and learning environment access provisioned within 24 hours of purchase
- Hand-built implementation playbook delivered alongside course access
Format: Text-based modules and chapters in the Art of Service learning environment, plus downloadable templates and worked examples for every chapter, plus the hand-built implementation playbook delivered alongside course access.
Time investment: Approximately 90 minutes per week over six weeks, designed for completion on weekends or quiet evenings.
How this compares to the alternatives
Unlike generic cybersecurity leadership courses, this program focuses exclusively on the unwritten rules, technical nuances, and stakeholder dynamics unique to quantitative finance environments.
Frequently asked
Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.