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patryk_slomka

Patryk S

@patryk_slomka

Data Engineer ML Specialist

Polonia
Inglés, Alemán, Holandés, Polaco
Parte de la información aparece en idioma inglés.
Sobre mí
Data engineer bridging technical execution and business strategy. My experience lies in building production ML pipelines for healthcare applications while managing international stakeholder coordination. I have a strong foundation in data engineering (Python, R, GCP) complemented by international business background. I possess proven skills in teamwork, insights presentation, and multilingual communication (Polish, English, German, Dutch). Passionate about solving complex problems in fast-paced collaborative settings.... Lee más

Habilidades

p
patryk_slomka
Patryk S
desconectado • 
Tiempo medio de respuesta: 1 hora

Revisa mis servicios

Sitios web y software con IA
I will develop ai agents and automation solutions with langchain
Consultoría de ingeniería de datos
I will build ml pipelines in python and gcp

Porfolio

Experiencia laboral

CapsicoHealth, Inc.

6 mos

Data Enginerr

Aug 2025 - Dec 20254 mos

- Architected complete end-to-end ML prediction pipeline integrating REDCap patient data retrieval, causal inference model execution (320+ models), and automated clinical decision support delivery, allowing to predict patient drug response in seconds. - Coordinated cross-functional collaboration with 4 stakeholders across Denmark, Netherlands, Germany, and US to align technical requirements with clinical workflows and regulatory constraints. - Developed RESTful API infrastructure using Flask and Python to orchestrate data flow between 320+ prediction models (Causal forest, XGBoost), implementing parallel processing for scalable model execution. - Built feature engineering pipeline handling medication normalization, dose standardization, and healthcare-specific data transformations using Python/R integration via secure subprocess management.

Data Engineering Intern

Jun 2025 - Aug 20252 mos

- Supported developing and validating 8 causal inference models (Causal forest, XGBoost) for treatment effect predictions, establishing foundation for production healthcare ML system. - Engineered data validation framework ensuring input data quality for R-based statistical models, implementing type checking, range validation, and error tracking for patient records. - Created inference execution system integrating R statistical models with Python-based pipeline, automating previously manual model deployment and reducing execution time by implementing subprocess-based model calls. - Collaborated with clinical teams to translate medical domain requirements into technical feature specifications and model metadata schemas.