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Services / AI + Data

Senior technical capacity without the agency layer.

I work directly with teams that need to turn data, machine learning or generative AI into a useful business capability. The engagement can be a small diagnostic, a focused build, an architecture review or ongoing senior support.

Discuss your use case →
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DIRECT DELIVERY

Strategy → build → production

$5.84M+

business value influenced

targeting, recommendations, optimization and AI automation

15+

people mentored

Data Science and Data Analyst teams

10+

industry contexts

including automotive, telco, banking, insurance, ecommerce and forestry

What you can hire me for

Four ways to add senior capability.

AI / ML Product Build

From hypothesis to production capability.

Build a focused ML or GenAI capability around a real business outcome: recommendation, prediction, classification, RAG, conversational AI or automation.

  • Problem framing & data audit
  • Model / AI prototype
  • Evaluation plan
  • Production handoff or deployment path

Data Platform & Engineering

Make the data layer dependable enough to build on.

Design or repair ETL, analytical data models, cloud pipelines, GIS workflows, dashboards and operational data collection systems.

  • Source-to-consumption map
  • Data quality controls
  • ETL / ELT pipelines
  • Documentation & runbooks

AI Architecture Advisory

Decide what should be built before building it.

Architecture reviews for AI systems, RAG applications, recommendation platforms, model-serving workflows and the surrounding data infrastructure.

  • Architecture decision record
  • Trade-off analysis
  • Reference architecture
  • Delivery roadmap

Analytics & Decision Systems

Turn questions into measurable decisions.

KPI design, behavioral analysis, experimentation, segmentation, forecasting, dashboards and insight workflows that help business teams act.

  • Metric framework
  • Exploratory / diagnostic analysis
  • Decision dashboard
  • Actionable recommendations

Engagement design

Start with the smallest engagement that can answer the question.

01

Diagnostic Sprint

1–2 weeks

A bounded investigation when the problem, data quality or ROI is still uncertain.

02

Build Sprint

3–8 weeks

A focused production-oriented capability with a clear definition of done.

03

Fractional Technical Partner

Ongoing

Senior execution and architecture support without adding a full-time specialist immediately.

04

Advisory Review

Fixed scope

Independent review of an existing data, ML or GenAI architecture before a major investment.

Typical flow

A simple path from ambiguity to delivery.

01

Frame the business outcome

02

Inspect data and constraints

03

Choose the simplest viable approach

04

Prototype and evaluate

05

Productionize the useful part

06

Measure and iterate

Illustration for collaborative delivery

Good fit if you need a senior builder.

I am comfortable being hands-on in Python, SQL, cloud data systems and ML/AI while also communicating architecture, trade-offs and business implications to non-specialists.

Tell me what outcome you need.

The first conversation does not need a perfect specification. A business goal and the current constraint are enough to start.

Book a discovery call