Jobs / Summary

Freelance Data Science Engineer (Python & SQL)

Confidential company · Hamburg · Posted May 14, 2026

Public summary

This freelance opportunity involves working on project-based AI tasks for leading tech companies. Contributors design and solve complex data science problems requiring Python and SQL expertise, involving statistical analysis, machine learning, and big data processing. The role demands strong experience in Python data science libraries and frameworks, knowledge of GenAI technologies, and advanced English proficiency (C1+). Projects are part-time, non-permanent, with variable hours and compensation up to $58 per hour, depending on project scope and contributor level. Collaboration includes problem creation, validation, and solution documentation in realistic business contexts across various industries.

Salary

USD 58.00 - 58.00 hour

Responsibilities

Design and develop computational data science problems simulating real-world analytical workflows across multiple industries. Create Python programming challenges utilizing libraries such as Pandas, Numpy, Scipy, Scikit-learn, Statsmodels, Matplotlib, and Seaborn. Ensure problems are computationally intensive and reproducible with deterministic solutions. Address business challenges including customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Develop end-to-end data science pipeline problems from data ingestion to deployment considerations. Incorporate scenarios requiring big data and scalable computation. Verify solutions using standard data science methods and document clear problem statements with realistic contexts.

Qualifications

Minimum 5 years of hands-on data science experience with proven impact. Strong portfolio demonstrating real-world problem solving and publications. Expert proficiency in Python programming for data science and advanced statistical analysis and machine learning understanding. Expertise in SQL and database operations. Experience with GenAI technologies such as LLMs, RAG, prompt engineering, and vector databases. Familiarity with MLOps practices and modern ML frameworks including TensorFlow, PyTorch, and LangChain. High-level written English proficiency (C1 or above).

Skills

Python SQL Pandas Numpy Scipy Scikit-learn Statsmodels Matplotlib Seaborn Statistical Analysis Machine Learning GenAI Technologies LLMs RAG Prompt Engineering Vector Databases MLOps Model Deployment TensorFlow PyTorch LangChain English (C1+)