A tailored course, built for your situation
Faster path from compliance intent to SOC 2 artefact
A 199 course for data scientists who lead control validation and evidence collection
The situation this course is for
Most data scientists spend too many cycles interpreting controls, gathering evidence, and revising artefacts because the path from intent to implementation isn’t codified. That creates friction in audit timelines and dilutes technical leadership.
Who this is for
Data scientists in consulting or service firms who own or co-lead SOC 2 compliance artefacts, evidence collection, and control validation
Who this is not for
Entry-level analysts, external auditors, or professionals focused exclusively on ISO 27001 without SOC 2 exposure
What you walk away with
- Map SOC 2 control objectives directly to data system configurations
- Produce auditor-ready evidence with fewer review cycles
- Reduce time from control scoping to signed-off artefacts by 50%
- Anticipate auditor line items before evidence submission
- Automate recurring validation steps using templated workflows
The 12 modules (with all 144 chapters)
- What SOC 2 really requires of data systems
- Difference between design and operating effectiveness
- Control vs audit procedure: your role in each
- Mapping TSC to technical controls
- Key evidence types by category
- How auditors evaluate completeness
- Common misinterpretations of CC6.1
- Linking data access logs to access control proofs
- Config settings that satisfy encryption proofs
- Timing expectations for point-in-time vs period controls
- Documentation thresholds by auditor tier
- Planning for multi-year compliance cycles
- Parsing control narratives for technical intent
- Identifying data owners for each control
- Defining evidence scope early
- Creating reusable evidence checklists
- Assigning validation ownership
- Setting cadence for sample testing
- Using data lineage to prove completeness
- Flagging system changes early
- Documenting compensating controls
- Versioning control interpretations
- Building evidence traceability matrices
- Pre-audit walkthrough preparation
- Workflow design for automated evidence capture
- Matching control type to validation method
- Sampling strategies for large datasets
- Using scripts to validate access reviews
- Logging control execution attempts
- Automating evidence packaging
- Scheduling recurring control checks
- Integrating with ticketing systems
- Version control for validation logic
- Handling exceptions in validation runs
- Alerting on control drift
- Archiving results for future audits
- Structure of a complete evidence package
- Narrative clarity for technical proofs
- Including timestamps and ownership
- Presenting system outputs effectively
- Redacting sensitive data safely
- Linking evidence to control statements
- Using annotations to guide reviewers
- Formatting for multi-auditor review
- Versioning artefacts across cycles
- Common rejection reasons and how to avoid them
- Preparing cover memos for package delivery
- Tracking artefact status across deadlines
- Predicting auditor follow-up questions
- Building rebuttals into first submission
- Using past findings to strengthen evidence
- Creating reference libraries for common queries
- Preempting scope challenges
- Clarifying control boundaries in narratives
- Including context for edge cases
- Demonstrating consistency across periods
- Responding to sample failures gracefully
- Managing materiality thresholds
- Using peer reviews before submission
- Incorporating feedback into next cycle
- Identifying repeatable control patterns
- Building modular evidence templates
- Designing plug-in narratives
- Versioning templates over time
- Customising without over-engineering
- Sharing templates across teams
- Governance for template use
- Integrating templates with tooling
- Tracking template effectiveness
- Updating templates after audits
- Onboarding new staff using templates
- Measuring time saved per reuse
- Logging access in Databricks
- Capturing query history for review
- Enabling audit logs in Snowflake
- Using GCP Cloud Audit Logs
- Setting up alerts on anomalous access
- Exporting logs for evidence bundles
- Validating IAM configurations
- Proving encryption at rest
- Demonstrating segregation of duties
- Linking service accounts to controls
- Automating evidence retrieval
- Maintaining compliance in serverless
- Mapping control ownership clearly
- Setting expectations with platform teams
- Creating service level agreements for evidence
- Using Jira for control tracking
- Defining handoff points
- Running cross-team validation syncs
- Escalating blocked items
- Documenting delegation chains
- Managing turnover in control owners
- Auditor communication protocols
- Handling shared responsibilities
- Reporting up on control health
- Types of encryption relevant to SOC 2
- Documenting encryption in transit
- Proving encryption at rest
- Key management practices
- Access to decryption keys
- Tokenization as a control
- Data masking configurations
- Data retention enforcement
- Proving secure disposal
- Validating backup encryption
- Handling encryption exceptions
- Auditor expectations for cryptographic proof
- Writing scripts to validate configurations
- Using Python to parse logs
- Automating access review reports
- Scheduling validation jobs
- Integrating with CI/CD pipelines
- Building dashboards for control health
- Alerting on control failures
- Versioning test logic
- Validating script accuracy
- Handling false positives
- Auditor acceptance of automated tests
- Documenting automation for review
- Difference between Type 1 and Type 2
- Evidence depth required for each
- Timing of evidence collection
- Demonstrating operating effectiveness
- Sample size expectations
- Reporting on control exceptions
- Proving consistency over time
- Preparing management letters
- Responding to auditor inquiries
- Finalising the SOC 2 report draft
- Post-audit action planning
- Using findings to improve next cycle
- Monitoring updates to SOC 2 guidance
- Tracking changes in Trust Services Criteria
- Adapting to new auditor demands
- Updating control mappings annually
- Revising artefacts efficiently
- Training new team members
- Benchmarking performance across cycles
- Sharing wins with leadership
- Demonstrating ROI of compliance work
- Advocating for tooling investments
- Building reputation as a go-to expert
- Transitioning to leadership in compliance
How this maps to your situation
- Starting a new SOC 2 engagement
- Responding to auditor feedback
- Onboarding new clients or systems
- Preparing for annual renewal
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 3 hours per module, designed to be completed in parallel with active compliance work.
How this compares to the alternatives
Unlike generic SOC 2 overviews or certification prep, this course focuses specifically on accelerating the path from control requirement to validated artefact , tailored for data scientists who must deliver evidence efficiently.
Frequently asked
Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.