Independent data practice

Scattered data,
clear decisions.
Built to ship.

I'm a freelance data scientist and engineer. I take the messy data your business already has — and turn it into models, pipelines and dashboards your team can actually use.

Science · models & forecasting
Engineering · pipelines & infra
Analytics · metrics & reporting
What I do

Three roles, one engagement.

Most data problems don't fit neatly into one job title. I cover the full stack — from raw collection to the decision it informs — so you don't have to coordinate three contractors.

01 — Data Science

Models that answer questions

Predict, classify, segment, forecast. Built to be measured against a real baseline — not just demoed.

  • Forecasting & demand planning
  • Churn, risk & propensity models
  • Customer & product segmentation
  • Experiment design & A/B analysis
02 — Data Engineering

Pipelines that don't break

The plumbing that gets clean, trustworthy data to the right place on schedule — and tells you when something's wrong.

  • ETL / ELT & data warehousing
  • API & database integrations
  • Cloud deployment & automation
  • Data quality & monitoring
03 — Analytics

Numbers people act on

Dashboards and analysis that make the next decision obvious — defined around the metrics that actually move your business.

  • KPI & reporting dashboards
  • Exploratory & ad-hoc analysis
  • Metric definition & tracking
  • Self-serve reporting for your team
How it works

A clear path, every time.

No surprises and no lock-in. Each stage has a defined output you can review before we move on.

STEP 01

Scope

A short paid discovery, or a free intro call. We agree the question, the data available, and what a useful result looks like — in writing.

STEP 02

Build

I work in focused increments with regular check-ins. You see progress early; scope stays flexible without becoming a moving target.

STEP 03

Validate

Every model or pipeline is tested against a baseline and documented. We confirm it does the job before it goes anywhere near production.

STEP 04

Hand over

You get clean code, documentation, and a walkthrough — so the work keeps running whether I stay involved or not.

Toolkit

Tools I reach for.

Chosen to fit the problem and your existing setup — not the other way around.

Python SQL pandas / Polars scikit-learn PyTorch dbt Airflow Snowflake / BigQuery Postgres AWS / GCP Docker Power BI / Looker Streamlit Git
About

Hi, I'm Cloud.

I spent years working with data inside teams — and saw how often good data work stalls between the people who have the data and the people who need the answer.

Now I work independently with small and mid-sized businesses that need serious data capability without hiring a full team. You get one accountable person who can model the problem, build the pipeline, and explain the result in plain language.

I care about work that ships and keeps working after I leave. No black boxes, no jargon for its own sake — just clear, durable results.

Based inEuropean Union · remote-first
BackgroundData Science & IT
EngagementsProjects · Retainer · Advisory · Consulting
AvailabilityTaking new projects
LanguagesEnglish
Get in touch

Have data sitting unused?

Tell me what you're trying to figure out. I'll reply within two business days with whether — and how — I can help.

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