Data Science & Predictive Analytics
Turn historical data into forecasts, risk scores, predictions, segmentation, optimization models, and revenue decisions - delivered with evidence-tagged inputs, red-team review, and executive-ready output.
Where this pillar plugs into the KRYOS service stack.
KRDS Multi-Layer Data Asset Valuation
Value data across cost, market, income, utility, AI contribution, obsolescence, risk, and option value.
Service detailAdvanced Scenario Simulation & Stress Lab
P10/P50/P90 valuation bands, stress scenarios, sensitivity ranks, and failure triggers.
Service detail16 named deliverables in this pillar.
Each is engageable as a diagnostic, sprint, project, managed program, or board / investor advisory pack.
Predictive Modeling Sprint
Stand up a defensible predictive model on a real business question in weeks, not quarters.
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Predictive Modeling Sprint
Stand up a defensible predictive model on a real business question in weeks, not quarters.
Historical dataset, target variable definition, business question.
Data audit → feature engineering → model bake-off → evidence-tagged evaluation → executive readout.
Predictive Model Report with band intervals and sensitivity ranking.
Free Model-Feasibility Memo on one dataset.
CTOs, CDOs, revenue and operations leaders.
Demand Forecasting
Forecast demand at the SKU, region, or channel level with calibrated uncertainty.
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Demand Forecasting
Forecast demand at the SKU, region, or channel level with calibrated uncertainty.
Time-series of demand, exogenous drivers, promotions, calendar.
Stationarity audit → driver selection → hierarchical model fit → backtest → P10/P50/P90 forecast.
Forecast pack with bands, drivers, and exception triggers.
Free 12-month Forecast Snapshot on one product line.
Supply chain, planning, finance.
Churn Risk Modeling
Identify at-risk customers and the drivers behind departure, with attributable lift.
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Churn Risk Modeling
Identify at-risk customers and the drivers behind departure, with attributable lift.
Customer event history, cancellation labels, plan and usage data.
Cohort framing → behavioral feature build → propensity model → uplift testing → retention playbook.
Churn Risk Score plus Top-Driver Attribution Pack.
Free 90-day Churn Pulse on a cohort sample.
Revenue, customer success, finance.
Customer Lifetime Value Modeling
Probabilistic LTV that survives finance and investor scrutiny.
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Customer Lifetime Value Modeling
Probabilistic LTV that survives finance and investor scrutiny.
Transaction history, retention curves, margin assumptions.
Cohort decomposition → BG/NBD or survival model → margin overlay → band projection.
LTV Ledger with cohort-level P10/P50/P90 and CAC payback bands.
Free Cohort LTV Snapshot on one cohort.
CFOs, growth, investors.
Propensity / Next-Best-Action Modeling
Rank every account or customer by likelihood and expected value of the next action.
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Propensity / Next-Best-Action Modeling
Rank every account or customer by likelihood and expected value of the next action.
Behavioral events, conversion outcomes, action catalog.
Action framing → propensity ensemble → expected-value scoring → A/B harness design.
NBA Scoring Engine with action-by-segment recommendations.
Free NBA Pilot on one campaign.
Marketing, sales operations, revenue.
Pricing Elasticity Modeling
Quantify how price moves change demand, revenue, and margin under realistic constraints.
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Pricing Elasticity Modeling
Quantify how price moves change demand, revenue, and margin under realistic constraints.
Historical price, volume, promotions, competitor signals.
Price-history reconstruction → causal elasticity estimation → margin simulation → price-corridor recommendation.
Pricing Elasticity Report with corridor recommendations.
Free Pricing Leakage Snapshot on one product family.
Pricing, revenue, finance.
Fraud and Anomaly Detection
Detect rare, high-cost events with thresholded precision and explainable triggers.
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Fraud and Anomaly Detection
Detect rare, high-cost events with thresholded precision and explainable triggers.
Transactional or event streams, labeled or unlabeled.
Anomaly framing → unsupervised + supervised ensemble → threshold calibration → analyst workflow design.
Anomaly Detection Engine with case-routing playbook.
Free Anomaly Pulse on a 30-day window.
Risk, fraud, security, payments.
Risk Scoring Model
Defensible probability-of-event scoring across credit, compliance, or operational risk.
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Risk Scoring Model
Defensible probability-of-event scoring across credit, compliance, or operational risk.
Outcome history, candidate predictors, governance constraints.
Outcome framing → calibration → fairness review → backtest → monitoring plan.
Risk Score Model Card with monitoring SLA.
Free Risk-Score Feasibility Memo.
Risk, credit, compliance.
Causal Inference Analysis
Move beyond correlation - quantify the actual effect of an intervention.
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Causal Inference Analysis
Move beyond correlation - quantify the actual effect of an intervention.
Intervention log, outcomes, confounder candidates.
DAG construction → identification strategy → estimator selection → sensitivity analysis.
Causal Effect Report with sensitivity bounds.
Free Causal Framing Memo for one hypothesis.
Strategy, marketing, policy, ops.
Experiment Design / A-B Testing
Design tests that yield real answers - not under-powered theatre.
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Experiment Design / A-B Testing
Design tests that yield real answers - not under-powered theatre.
Hypothesis, success metric, expected effect size.
Power analysis → randomization design → guardrail metric selection → readout protocol.
Experiment Charter with stop conditions and decision rules.
Free A/B Power Calculator review.
Growth, product, ops.
Optimization Modeling
Allocate budget, routes, inventory, or capacity against multi-constraint objectives.
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Optimization Modeling
Allocate budget, routes, inventory, or capacity against multi-constraint objectives.
Decision variables, constraints, objective function, current allocation.
Constraint capture → solver selection → sensitivity analysis → rollout plan.
Optimization Engine with re-solve cadence.
Free Allocation Audit on a single decision.
Operations, finance, marketing, supply chain.
Uplift Modeling
Target the customers who will respond because of the action - not those who would convert anyway.
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Uplift Modeling
Target the customers who will respond because of the action - not those who would convert anyway.
Treatment-and-control history, outcomes.
Causal framing → meta-learner selection → segment qualification → deployment harness.
Uplift Targeting Score per customer.
Marketing, retention, sales.
Survival / Time-to-Event Modeling
Estimate the timing of churn, conversion, default, or failure with proper censoring.
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Survival / Time-to-Event Modeling
Estimate the timing of churn, conversion, default, or failure with proper censoring.
Event-time histories with censoring flags.
Survival framing → hazard model fit → covariate analysis → calibrated time-band output.
Time-to-Event Hazard Curves with intervention timing.
Customer success, finance, equipment reliability.
Feature Store Strategy
Define the reusable, governed feature layer that lets every model team move faster and safer.
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Feature Store Strategy
Define the reusable, governed feature layer that lets every model team move faster and safer.
Existing pipelines, model registry inventory, governance constraints.
Feature inventory → ownership map → governance design → migration roadmap.
Feature Store Blueprint with cost-and-control model.
CDOs, AI/ML platform leads.
Explainability and Transparency Pack
Make every model decision defensible to regulators, customers, and the board.
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Explainability and Transparency Pack
Make every model decision defensible to regulators, customers, and the board.
Production model, recent predictions, governance scope.
Method selection → local + global explanation generation → fairness review → disclosure pack.
Model Transparency Pack with SHAP / counterfactuals / fairness audit.
Compliance, risk, customer-facing AI teams.
Model Validation and Monitoring
Continuous evidence that models in production are still doing what was promised.
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Model Validation and Monitoring
Continuous evidence that models in production are still doing what was promised.
Live model traffic, ground-truth feedback loop.
Drift sensor design → performance dashboard → alert routing → revalidation cadence.
Model Monitoring Console with revalidation SLA.
ML platform, risk, regulated AI teams.
The KRYOS standard.
Evidence-tagged inputs
Every claim carries a provenance and quality tag - no untraceable assertions.
Red-team review
Independent adversarial challenge before delivery - by design, not by exception.
Executive-ready output
Decision packets, not slide decks. Sized for the role that has to act.
No unsupported guarantees
We do not promise valuations, funding, or regulatory outcomes. We deliver evidence.
One Hypercube. Six pillars.
Begin with a forensic data asset assessment.
A focused engagement that maps your data estate, scores assets against KRYOS frameworks, and produces a board-ready brief on what to recognize, value, productize, and capitalize.