A tailored course, built for your situation
Mastering MiFID II for Data Scientists in Financial Services
Build compliant, high-velocity data workflows with confidence
$199 one-time
24-hour access provisioning
30-day money-back guarantee
Hand-built implementation playbook
12 modules. 12 chapters per module. 144 chapters total.
12 modules, each with 12 chapters (144 chapters total), text-based, plus downloadable templates and a hand-built implementation playbook delivered alongside course access.
Stop rebuilding data pipelines to meet compliance checklists at the last minute.
The situation this course is for
Data scientists in regulated financial institutions often work in isolation from compliance requirements until late in the delivery cycle. This leads to rework, delayed deployments, and friction between technical and regulatory teams. The lack of shared language slows velocity and increases risk exposure.
Who this is for
A senior Data Scientist in a global financial institution who owns or influences data pipeline design and must navigate MiFID II reporting constraints without sacrificing innovation or speed.
Who this is not for
Entry-level analysts, compliance auditors without data modeling roles, or developers working outside regulated financial data environments.
What you walk away with
- Turn regulatory requirements into actionable data schema rules from day one
- Reduce time from model development to compliance approval by up to 65%
- Produce audit-ready documentation automatically embedded in pipeline outputs
- Align with legal teams using shared, technical artefacts instead of meetings
- Gain recognition as the go-to practitioner for compliant data innovation
The 12 modules (with all 144 chapters)
Module 1. Why MiFID II Now Matters in Data Pipeline Design
Understand how recent supervisory findings are reshaping expectations for data transparency and auditability in algorithmic trading and client reporting workflows.
12 chapters in this module
- Mapping MiFID II's Article 12 to data provenance requirements
- How transaction reporting rules affect model output logging
- The impact of RTS 23 on data retention and access controls
- Linking best execution obligations to feature engineering
- Regulator expectations for explainability in automated decisions
- How Brexit changed cross-border data flows under MiFID
- Common misalignments between data science teams and compliance units
- Case study: Rejected filing due to missing data lineage
- Timeline of major ESMA enforcement actions since the current cycle
- How national regulators apply MiFID II differently
- The role of data scientists in pre-audit risk assessments
- Building awareness of MiFID II into sprint planning
Module 2. From Code to Compliance: Bridging the Gap
Learn to translate technical work into regulatory language without slowing down development cycles.
12 chapters in this module
- Turning Jupyter notebooks into compliance-ready documentation
- Automating metadata tagging to meet RTS 22 requirements
- Designing model cards that satisfy MiFID II disclosure needs
- How to structure DAGs for audit-friendly traceability
- Embedding data dictionaries in pipeline outputs
- Creating version-controlled change logs for reporting models
- Translating feature engineering decisions for non-technical reviewers
- Building compliance checkpoints into CI/CD workflows
- Generating standardized logs for transaction reporting
- Documenting data transformations in plain business language
- Using schema versioning to support regulatory queries
- Aligning data drift detection with periodic review cycles
Module 3. Data Provenance and Regulatory Audit Trails
Implement systems that automatically generate defensible, end-to-end data lineage.
12 chapters in this module
- Defining minimum viable lineage for MiFID II purposes
- Instrumenting pipelines to capture origin and transformation steps
- Storing lineage data in queryable, regulator-accessible formats
- Linking raw input sources to final reported metrics
- Handling third-party data feeds in audit trails
- Designing lineage retention policies aligned with RTS 23
- Integrating lineage capture with existing observability tools
- Validating completeness of lineage records pre-submission
- Redacting sensitive fields without breaking traceability
- Benchmarking lineage coverage across peer institutions
- Using lineage maps in internal audit preparation
- Responding to follow-up questions from regulators
Module 4. Best Execution Analysis in Practice
Structure data workflows to support transparent, defensible best execution reporting.
12 chapters in this module
- Defining benchmark routes for execution quality measurement
- Capturing timestamp precision required under RTS 27
- Aggregating venue performance data for periodic review
- Calculating slippage metrics across asset classes
- Designing alerts for outlier execution patterns
- Mapping trading decisions to client order characteristics
- Handling dark pool and systematic internaliser data
- Integrating market impact models into execution strategy
- Producing regulator-ready summaries of execution quality
- Automating comparisons across broker-dealer performance
- Documenting methodology for internal sign-off
- Updating execution logic based on performance feedback
Module 5. Transaction Reporting Compliance
Ensure accurate, complete, and timely transaction reporting through robust data engineering.
12 chapters in this module
- Understanding the 61 fields required in each report
- Validating client identifier formats (LEI, ISIN, MIC)
- Mapping internal trade IDs to regulatory submission records
- Handling complex instruments like derivatives and ETFs
- Reconciling internal systems with external reporting outputs
- Implementing automated error detection for missing fields
- Designing fallback processes for system outages
- Tracking latency between execution and report submission
- Auditing report accuracy across randomized samples
- Logging corrections and amendment histories
- Integrating with trade repository interfaces
- Generating test reports for dry-run validation
Module 6. Algorithmic Trading and RTS 6 Compliance
Meet pre-deployment and ongoing monitoring requirements for automated strategies.
12 chapters in this module
- Defining when a model qualifies as algorithmic trading
- Documenting strategy intent for regulatory filing
- Implementing kill switch logic in production pipelines
- Monitoring for unintended market impact or spoofing
- Tracking thresholds for volume or order-to-trade ratios
- Automating anomaly detection in trading behavior
- Scheduling periodic performance reviews
- Logging changes to algorithm parameters or logic
- Integrating with market surveillance systems
- Preparing pre-deployment impact assessments
- Capturing stress test results for audit
- Responding to regulator requests for backtesting
Module 7. Client Classification and Data Handling
Ensure proper handling of client data based on MiFID II categorization rules.
12 chapters in this module
- Storing and validating client professional status flags
- Managing enhanced data permissions for retail clients
- Applying differential logging based on client type
- Tracking consent for data usage in model training
- Enforcing access controls for sensitive client segments
- Documenting data minimization practices
- Handling cross-border client data flows
- Updating classifications based on behavioral signals
- Auditing access to high-risk client records
- Generating compliance reports for internal review
- Aligning with GDPR in dual-impact scenarios
- Designing declassification workflows for status changes
Module 8. Cost and Charges Transparency
Structure data systems to support accurate, auditable cost disclosures.
12 chapters in this module
- Capturing all sources of implicit and explicit costs
- Aggregating fees across execution, custody, and advice layers
- Calculating performance-impacting deductions
- Time-weighting charges for accurate reporting
- Linking cost data to specific client portfolios
- Validating accuracy of cost attribution logic
- Generating standardized cost summaries for clients
- Building reconciliation checks between systems
- Auditing cost calculations for sample clients
- Updating methodologies when new fee types emerge
- Documenting assumptions in cost modeling
- Supporting regulator inquiries with full cost trails
Module 9. Integrating Compliance into Agile Development
Embed regulatory requirements into sprint cycles without slowing innovation.
12 chapters in this module
- Adding MiFID II criteria to user story acceptance checks
- Creating compliance-ready definition of done
- Running joint tech-compliance grooming sessions
- Tracking compliance debt alongside technical debt
- Using automated linting for regulatory keywords
- Building compliance dashboards for team visibility
- Shifting compliance reviews left in the pipeline
- Running mock audits during sprint reviews
- Inviting compliance partners to retrospectives
- Documenting decisions in shared repositories
- Measuring velocity impact of compliance integration
- Celebrating compliance wins in team standups
Module 10. Cross-Functional Alignment Strategies
Work effectively with legal, compliance, and operations teams on shared goals.
12 chapters in this module
- Translating data concepts for non-technical stakeholders
- Using visual diagrams to explain pipeline logic
- Scheduling regular sync points with compliance teams
- Creating shared terminology glossaries
- Running joint training sessions on MiFID II updates
- Building trust through early transparency
- Escalating ambiguities before implementation
- Co-developing templates for recurring reports
- Establishing feedback loops for process improvement
- Managing differing priorities across functions
- Leveraging overlap in data quality requirements
- Recognizing team efforts in cross-functional wins
Module 11. Automating Regulatory Readiness
Build systems that continuously validate compliance posture.
12 chapters in this module
- Designing automated checks for RTS 22 compliance
- Validating data retention policies across storage layers
- Monitoring access logs for audit trail completeness
- Generating self-assessment reports for senior management
- Alerting on potential breaches of trading thresholds
- Running synthetic transaction tests
- Benchmarking compliance posture against peers
- Automating documentation for annual renewals
- Integrating with GRC platforms for centralized visibility
- Logging responses to compliance exceptions
- Updating rulesets when regulations evolve
- Testing failover compliance modes
Module 12. Future-Proofing Your Compliance Workflow
Stay ahead of evolving expectations with adaptable, maintainable systems.
12 chapters in this module
- Tracking upcoming regulatory consultations
- Participating in industry working groups
- Building modular components for rapid adaptation
- Documenting design rationale for future teams
- Creating onboarding materials for new hires
- Maintaining a living compliance knowledge base
- Using retrospective insights to refine processes
- Measuring the cost of compliance over time
- Sharing best practices across departments
- Advocating for tooling investments
- Mentoring junior data scientists in compliance
- Positioning yourself as a leader in responsible innovation
How this maps to your situation
- Data Scientists at financial institutions balancing innovation with regulatory constraints
- Teams rebuilding pipelines due to late compliance input
- Organizations preparing for unannounced regulatory reviews
- Practitioners seeking recognition as compliance-competent technologists
Before vs. after
Before
Spending weeks reworking models after audit feedback, facing pressure to move fast without breaking rules, struggling to explain technical choices to compliance teams.
After
Shipping compliance-ready outputs on first submission, reducing approval cycles by up to 65%, and gaining recognition as a trusted partner in regulated innovation.
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: 90 minutes of focused reading and implementation planning, designed for completion on a Sunday morning.
If nothing changes
Without structured integration of MiFID II into data workflows, teams risk delayed deployments, regulatory scrutiny, and erosion of trust between technical and compliance functions, slowing every future initiative.
How this compares to the alternatives
Unlike generic compliance courses or dense regulatory PDFs, this course gives you actionable, code-adjacent workflows used by data scientists at leading banks to meet MiFID II without sacrificing velocity.
Frequently asked
Do I need a legal background to benefit from this course?
No. The course is designed for technical practitioners who need to meet regulatory standards without becoming lawyers. We translate requirements into data design choices.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Will this help me if I don’t work directly on trading systems?
Yes. MiFID II impacts any data workflow tied to client advice, order execution, or market reporting, even indirect ones. The principles apply across capital markets data.
$199 one-time. 90 minutes of focused reading and implementation planning, designed for completion on a Sunday morning..
Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.
30-day money-back guarantee·
144 chapters·
Hand-built playbook included·
Account access within 24 hours