Sub-function
Data Science & Modeling
Owns model work end to end inside Research & Development. Runs 3 lines across 19 stations, drains the repeatable share into the DATA-ANALYTICS tower, and holds 4 human gates.
Estate rating
BBB
72 / 100
Training, validation and drift detection are fully agentic. Promoting a model to production requires a named reviewer, because a model in production is a decision-maker.
Agents
8
Lines
3
Units / wk
15,032
Timetable vs actual
13.8h → 12.4h
Cost / unit
$14
was $46
Run-rate saving
$24.6M
annualized at this volume
The 8 agents running this sub-function
Grouped by what they are for, not by where they sit. The agent org is process-shaped.
Modeling Orchestrator
Owns the data science & modeling lane end to end. Sequences the other agents, holds the timetable, and decides what surfaces to a human.
ceiling A3 · escalates to Escalates to Director, Data Science when the unit falls outside the decision envelope or confidence drops below the floor.
Feature Engineering Agent
Runs the repeatable portion of data science & modeling inside the shared transaction spine at spine cost and spine controls.
ceiling A3 · escalates to Escalates to Director, Data Science when the unit falls outside the decision envelope or confidence drops below the floor.
Model Training Agent
Executes the data science & modeling step it owns, posts its evidence, and hands the unit to the next stage.
ceiling A3 · escalates to Escalates to Director, Data Science when the unit falls outside the decision envelope or confidence drops below the floor.
Validation Agent
Executes the data science & modeling step it owns, posts its evidence, and hands the unit to the next stage.
ceiling A3 · escalates to Escalates to Director, Data Science when the unit falls outside the decision envelope or confidence drops below the floor.
Explainability Agent
Executes the data science & modeling step it owns, posts its evidence, and hands the unit to the next stage.
ceiling A3 · escalates to Escalates to Director, Data Science when the unit falls outside the decision envelope or confidence drops below the floor.
Drift Monitoring Agent
Watches data science & modeling continuously. Detects drift, quantifies it, and routes what matters without waiting for a reporting cycle.
ceiling A3 · escalates to Escalates to Director, Data Science when the unit falls outside the decision envelope or confidence drops below the floor.
Model Governance Agent
Holds the rules that bind every other agent in data science & modeling. Versions them, tests them against live decisions, and blocks work that breaches them.
ceiling A3 · escalates to Escalates on any decision that would breach a live policy version, with the clause cited.
Data Science & Modeling Challenger Agent
Adversarial reviewer for data science & modeling. Argues the opposite case on every position and flags where the evidence does not carry the claim.
ceiling A3 · escalates to Escalates when a ratified position is still running against a break condition it flagged.
Estate rating breakdown
Seven control dimensions. Judgment readiness runs against autonomy on purpose.
People
What the humans stopped doing, and what they do now.
Redeployed into scenario work and strategy authoring review.
Lines running in this sub-function
Each line is a workflow. Click a line to walk it station by station.
Strategy positions this sub-function holds
An agent that only executes is a robot. These are the calls it made, the argument against each one, and what would prove it wrong.
Data Science & Modeling Operating Position
In challengev2Where should the autonomy ceiling for data science & modeling sit over the next four quarters, and what evidence would justify moving it?
Hold the ceiling at A3 for data science & modeling. Training, validation and drift detection are fully agentic. Promoting a model to production requires a named reviewer, because a model in production is a decision-maker. Raise it only after two consecutive quarters where the override rate stays under five percent and every override has a written cause.
confidence
59%
The challenge — Data Science & Modeling Challenger Agent
Data Science & Modeling Challenger Agent argues the recommendation leans on 5 quarters of data from a period with no volume shock. The confidence band overlaps the alternative, and the position does not say what it would take to be wrong. Recorded as a dissent, not a block.
Break conditions
- ·Override rate rises above 13 percent for two consecutive months
- ·Cost per model stops falling while volume keeps rising
- ·A control failure in this lane reaches a customer or a regulator
Evidence gaps
- ·No external comparator on a like-for-like unit definition
- ·Exception cases under $22k are sampled, not fully measured
| Alternative considered | Cost | Risk | Verdict |
|---|---|---|---|
| Hold the current position | $850k run rate | Known and priced. Cedes ground if comparators move faster. | live |
| Raise the ceiling one level now | $723k to build controls | Override rate is 7 percent; raising the ceiling before that settles imports the error into production. | rejected on evidence |
| Move the exception tail to the spine | $860k transition | Loses local context. Rework risk on the cases that are hardest to recover. | under review |
Policy register
The rules the agents above are bound by. Version, owner, approver, and the agents each rule constrains.
| Ref | Rule | Scope | Owner agent | Approved by | Version | Status |
|---|---|---|---|---|---|---|
| RD5-POL-200 | Data Science & Modeling Decision Envelope Agents in this lane may act without a human when the model sits inside the stated value, risk and confidence envelope. Outside it, the unit holds at a gate with a named approver and a running clock. binds 4 agents · EU · UK · US | envelope | Model Governance Agent | Director, Data Science | v2.7 | Active |
| RD5-POL-201 | Data Science & Modeling Evidence Standard Every autonomous decision writes inputs, the rule version applied, the model and prompt version, the output and a reversal path. An action with no evidence record is treated as a control failure, not a fast decision. binds 4 agents · US · Canada | evidence | Model Governance Agent | Director, Data Science | v2.3 | Superseded |
| RD5-POL-202 | Data Science & Modeling Escalation Rule Escalation is mandatory when confidence falls below the floor, when two options sit inside the confidence band, or when a break condition on a ratified position fires. Director, Data Science owns the response clock. binds 4 agents · US · Canada | escalation | Model Governance Agent | Director, Data Science | v5.0 | Active |
| RD5-POL-203 | Data Science & Modeling Autonomy Ceiling The ceiling for this lane is 83 on the platform scale. Training, validation and drift detection are fully agentic. Promoting a model to production requires a named reviewer, because a model in production is a decision-maker. The ceiling is a governance decision, not a technical limit, and only Director, Data Science can propose moving it. binds 4 agents · LATAM · US | ceiling | Model Governance Agent | Director, Data Science | v1.7 | Active |