Creatives Data
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Data / Data ScienceData practice since 2018
FeaturesModelledEvaluated

From features to models that ship.

Data alone does not create advantage and a model in a notebook creates none. Data science is the disciplined loop from feature engineering through model development to evaluation and deployment, then back again, so prediction runs in production and improves rather than staying an experiment.

FeaturesModelsEvaluationDeploymentMonitoringGovernance
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Brands we have shapedCAINDEZBAK30 international design awards
Data scienceModel · v1
One modelFeatures · Evaluate · Operate
Brands we have shaped
Crispy AsianInsperaDeylarZubyArzu KaprolWhite Istanbul Photography
What data science covers

A loop, not a one off.

Dashboards explain the past; data science engineers the next decision. We treat modelling as a governed loop, feature engineering, development, evaluation and deployment, with retraining designed in, so a model earns trust and keeps it as the world changes.

  • 01 · FeaturesThe base

    Data and feature engineering

    Clean, scalable pipelines and engineered features come first, because a model is only as strong as the data it learns from.

    What you get
    • Feature engineering
    • Pipelines
    • Clean datasets
    • DataOps
  • 02 · ModelThe build

    Model development

    Models built for the problem, from classification and forecasting to recommendation and anomaly detection, engineered for interpretability rather than novelty.

    What you get
    • Classification
    • Forecasting
    • Recommendation
    • Interpretability
  • 03 · EvaluateThe check

    Validation and governance

    Cross validation, controlled testing, bias and fairness checks and explainability, so a model is trusted before it reaches production.

    What you get
    • Cross validation
    • Controlled testing
    • Bias checks
    • Explainability
  • 04 · OperateBuilt to last

    Deployment and the retrain loop

    Versioning, drift detection and monitoring operationalise the model and feed evaluation back into features, so intelligence keeps improving rather than decaying.

    What you get
    • Deployment
    • Versioning
    • Drift detection
    • Retraining
The lifecycle, on one page

Feature, model, evaluate.

Features, models and evaluation are defined as one loop, so a validated model deploys and its monitoring feeds the next round of features rather than ending at a report.

Models and experiments
FeaturesEngineer
ModelsTrain
EvaluationValidate
Loop
traintestvalidate
Model loop
Model loop · features, models, evaluationCreatives Data · data team
How we work

How we build models.

A path from feature engineering to a live retrain loop, so prediction reaches production governed rather than left in a notebook.

  • 1

    Feature engineering

    Clean pipelines and engineered features prepared for modelling.

    Prepared
  • 2

    Model development

    Models built for the problem and interpretability.

    Built
  • 3

    Validation

    Cross validation, bias checks and explainability before release.

    Validated
  • 4

    Deploy and retrain

    Deployment, drift detection and a retraining loop wired in.

    Operated
What we build

Science, stage by stage.

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  • Feature engineering

    Feature engineering

    Engineered features on clean, scalable pipelines.

    FeaturesPipelines
  • Predictive model

    Predictive model

    A model built for the problem and interpretability.

    ModelsPrediction
  • Validation framework

    Validation framework

    Cross validation, bias checks and explainability.

    ValidationGovernance
  • Deployment and retrain

    Deployment and retrain

    Versioning, drift detection and a retraining loop.

    DeployRetrain
Recognition

Work that gets noticed.

  • Awards
    30

    International design awards

    Including Communicator, Davey, W3 Gold and Silver, Horizon and London Design Awards.

  • Scope
    End to end

    Feature to production

    Feature engineering, modelling, validation and deployment, delivered by one team.

  • Approach
    Production first

    Governed

    We build models that ship and retrain, not experiments that stall.

A model that never ships predicts nothing.

Creatives Data · data team
Related services

Where data science goes next.

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Pick a way to begin

Three ways to start.

Let us put your models into production.

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