Lilya YAHIAOUI

A typical week in my work as a Data Scientist looks like:

• checking data quality issues before they break forecasts • debugging feature pipelines in PySpark • retraining models and tracking experiments in MLflow • explaining results to non-technical stakeholders •...

“You don’t need a full ML team”

Many teams don’t need a full ML department.

They need: • one clear use case • clean data pipelines • a reliable first model

I help teams get there efficiently, without overbuilding.

Open to short-term or part-time collaborations.

🧠 Need a data scientist who understands both models and product?

I work with product and engineering teams to turn machine learning into features users actually benefit from.

My background includes: • Improving search and discovery for e-commerce platforms • Building chatbots...

I help teams turn messy business data into production-ready machine learning solutions.

My experience spans the full ML lifecycle: • Exploratory data analysis & feature engineering (Pandas & PySpark) • Training and evaluating ML models • Building scalable data pipelines •...