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I will build ml pipelines in python and gcp
Data Engineer ML Specialist
Data engineer bridging technical execution and business strategy. My experience lies in building production ML pipelines for healthcare applications while managing international stakeholder coordinati...
À propos de ce service
Need a reliable ML pipeline that actually works in production?
I build clean, production-ready machine learning pipelines and data engineering solutions in Python.
What I deliver:
- Complete data pipelines (ETL, feature engineering, validation)
- ML model development & deployment
- REST API development (Flask / FastAPI)
- Docker containerization
- Clean, well-documented code + notebook + report
Technologies I use:
Python, R, SQL, Flask/FastAPI, Docker, GCP, ML (XGBoost, Causal Forest)
Perfect for:
Startups moving from notebook to production, healthcare data projects, fraud detection, business analytics.
I only accept projects I can deliver with high quality. Please message me before ordering so we can discuss scope and make sure its a good fit.
Mon portfolio
FAQ
What is your experience with production ML pipelines?
I have real production experience from US stratup, where I architected end-to-end ML pipelines that scaled to 320+ causal inference models serving clinical teams. I focus on reliable, maintainable solutions rather than just notebooks.
What technologies do you use?
Python (primary), SQL, Flask/FastAPI, Docker, Google Cloud Platform (GCP), XGBoost, Causal Forest, and tools like Pandas, Scikit-learn. I can also work with BigQuery, PostgreSQL, and basic Spark.
Can you work with my existing Jupyter notebooks or code?
Yes! I can take your notebooks, refactor them into clean production code, add proper error handling, validation, and deployment structure.
Do I receive the full source code?
Yes, you get complete, well-documented source code that you fully own. All packages include clean Python code and documentation.
What do you need from me to start the project?
A clear description of your goal, sample data (or data format), and any specific requirements (e.g. cloud platform, output format). The more details you provide, the better and faster I can deliver.
Do you provide support after delivery?
Yes. The Premium package includes 14 days of post-delivery support. For Standard and Basic packages, I offer reasonable follow-up questions within the first week.
Can you deploy the pipeline to the cloud?
Yes, especially on GCP (my strongest platform). I can also guide deployment on AWS or Azure. Full cloud deployment with Docker is included in the Premium package.
Are you suitable for beginners or non-technical clients?
Yes. I explain everything clearly and provide documentation. I’m happy to work with non-technical clients as long as we discuss the scope upfront.
