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Data Science
— models that ship

Forecasting, prediction and optimisation models built on your data and deployed with MLOps — from classical machine learning to GenAI-augmented analytics — with monitoring for drift and value.

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Data Science

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Topics we cover

Data scienceMachine learningForecastingPredictive analyticsOptimisationAnomaly detectionIoT analyticsTime-seriesFeature engineeringMLOpsModel monitoringDrift detectionExplainability (SHAP)Causal inferenceExperimentation / A/B testingSynthetic dataGenAI + ML

Status quo · late 2026

What has changed — and why it matters now

ML and GenAI converge

LLMs generate features, explain models and orchestrate classical predictors; classical ML still wins on tabular forecasting and cost.

Production is the bar

Notebooks are not deliverables — registries, pipelines, monitoring and retraining are.

Causality and trust

Explainability, fairness and causal methods are required for decisions that affect customers and staff.

How we approach it

Our method for Data Science

01FrameDecision, metric, baseline, value hypothesis.

02Data & featuresFeature engineering, leakage checks, feature store.

03ModelBaselines first; gradient boosting, time-series, deep learning where justified; experiment tracking.

04DeployBatch or real-time serving, CI/CD, registry, approvals.

05MonitorDrift, performance, business value; retraining triggers.

In depth

Typical use cases

Demand & financial forecasting

Hierarchical time-series, scenario planning.

Predictive maintenance / IoT

Sensor analytics, anomaly detection, remaining useful life.

Customer models

Churn, propensity, lifetime value, next-best-action.

Risk & fraud

Scoring, anomaly detection, explainable decisions.

Optimisation

Pricing, scheduling, routing with OR + ML.

What you get

Deliverables

Regression & forecast modelsML pipelinesIoT analyticsMLOps deploymentDrift detectionModel performance monitoring

Technology-agnostic

Platforms we work across

We design for the outcome first and choose the platform second — across Microsoft, AWS and Google Cloud, and every major AI provider.

Azure ML & Fabric Data ScienceDatabricksAWS SageMakerGoogle Vertex AIMLflowscikit-learn / XGBoost / PyTorchProphet / Nixtla

More Data services

Data Lake Architecture Data Engineering Data Analytics Data Governance Data Mesh, Fabric & API Access

Ready to talk about Data Science?

One email reaches the architects and engineers who will do the work. We reply within one working day.

info@uspc.co.uk Contact page

Data Science— models that ship