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
•...
🧠 Hi Contra, alongside retail forecasting, I’ve worked on applied NLP and computer vision projects that go beyond experiments and turn into real solutions.
I’ve built:
• Review rating prediction with BERT
• Text summarization using FLAN-T5
• Sign language classification
• Fruit...
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...